Sustainability Assessment Model

Abstract

The concept of sustainability, in the way we understand the term now, first appeared in 1987, within the Brundtland Report, defined as “to meet the needs of the present generation without compromising the ability of future generations to meet their own needs.” Later, as the concept gained popularity, hundreds of definitions were proposed, in academic debates and business arenas, referring to a more ethical, more green, and more transparent way of doing business. Today, the label of “sustainable” is a bottom-line requirement: as a matter of fact, Sustainability has become a common basic goal for many national and international organizations including industries, governments, NGOs, and universities. However, in spite of the nearly universal recognition that Sustainability has received, companies still struggle with the full understanding of the concept and with its financial viability.

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3.1 Introduction

The concept of sustainability, in the way we understand the term now, first appeared in 1987, within the Brundtland Report, defined as “to meet the needs of the present generation without compromising the ability of future generations to meet their own needs.” Later, as the concept gained popularity, hundreds of definitions were proposed, in academic debates and business arenas, referring to a more ethical, more green, and more transparent way of doing business. Today, the label of “sustainable” is a bottom-line requirement: as a matter of fact, Sustainability has become a common basic goal for many national and international organizations including industries, governments, NGOs, and universities. However, in spite of the nearly universal recognition that Sustainability has received, companies still struggle with the full understanding of the concept and with its financial viability.

So the first problem lies with understanding: in the jungle of definitions, and to be able to point out the link with mass customization, we try hereinafter to set some cornerstones, exploring the three sustainability pillars, economical, environmental, and social, and proposing practical indexes to build-up an effective assessment model. The assessment model represents a quantitative (meaning numbers: clear, reliable, and exploitable) measurement of environmental, economic, and social performances: the use of numbers will transform the well-recognized but sometimes vague concept of sustainability into a powerful tool that decision-makers can understand and apply in their everyday work.

The development of this sustainability assessment model (SAM), meant to be a practical and usable tool, lays its foundations on an extensive literature review: this revealed a considerable amount of methodologies addressing the evaluation of sustainability of product, manufacturing system, and supply chain. However, indicators found in the literature proved to be unbalanced or too much qualitative to be concretely applied, and, additionally, to be incomplete at least at social level. The main innovation here promoted lies in the development of an holistic set of indicators capable to evaluate sustainability considering the Stable Solution Space (as defined in Chap. 2) as a whole: the product is produced within a defined manufacturing system and delivered by a supply network, and all these entities are involved in determining the final sustainability level of the Solution Space.

The assessment results have been related to a single unit of product, thus fostering an immediate perception of the burden set to the environment, society, and economy connected to the final act of buying.

Section 3.2 deals with the explanation why some indicators have been chosen rather than others, while Sect. 3.3 presents the actual indicators and their calculation formula.

3.2 Assessment Indexes Selection

The first step is to define the criteria used in the identification of the suitable indexes. The identification activity then started with a literature review of sustainability assessment indexes trying to figure out those most frequently used to measure the performances of solution spaces (product, production system, and supply chain). This preliminary list highlighted that many sustainability areas could be analyzed through indicators taken from existing sources, but also that some indexes should be created ad hoc for the our SAM.

3.2.1 Selection Criteria

This section presents the criteria used in the selection of the sustainability indicators. Since the literature analysis highlighted a considerable amount of existing indexes used by academic institutions and industries for the evaluation of sustainability performances, the need for a criteria allowing the selection of the most suitable indicators as far as the assessment model aim is concerned emerged soon. For this reason, a list of selection criteria has been developed:

• Measurable: the indicator is measurable. The measured impact and its sources can be translated and conveyed in a quantitative measure.

• Understandable: the indicator is easy to understand, even by people who are not experts. People do not end up arguing over what the indicator means.

• Exploitable and Relevant: the indicator measures something that is important to the company implementing it for highlighting existing problems and enhancing its performances.

• Balanced and fitted: the selected indicators provide a comprehensive view of the key issues. There isn’t any overlapping over same issues or incoherence between indicators.

• Potential for influencing change: the evidences collected will be useful for the decision-makers inside the companies. The indicators enable decision-makers to understand what the necessary corrective actions are.

• Reliable: the process that transforms the input data into the final indicator outcome provides a measure that can be trusted.

• Achievable, based on accessible data: the information is available or can be gathered while there is still time to act.

• Comprehensive (product/process/supply chain): an indicator is desirable to be applicable to the different design entities: product, manufacturing, and supply chain. Including all the design level, the indicator allows the overall assessment of the sustainability and the mass customization of the product system.

• Flexible: an indicator must be flexible and multipurpose, that is, it can be applied to different kind of products, production process, and supply chains.

• Established: an indicator, and the way to calculate it, is desirable to show a large consensus in the academic and industrial environments especially if the indicator addresses some sustainability or mass customization areas that are studied by long time and the industrial application is well established.

3.2.2 Identification of the Assessment Indexes

This section is meant to present the identification of the assessment indexes performed through either the selection of the existing indicators (using the above-listed criteria), their adaptation, or thanks to the development of ad-hoc indicators. The presentation of the indicators selection is carried out into the three sustainability areas: Environmental, Economic and Social.

3.2.2.1 Environmental Indicators Selection

Thanks to the lifecycle assessment (LCA) methodology, the evaluation of the environmental performances of products and companies is quite an established issue. The state of the art analysis on the environmental indicators provided a very long list of environmental indexes. In this analysis, different sources of environmental indicators have been considered namely:

• Literature: i.e., Azapagic and Perdan (2000); Krajnc and Glavic (2003); Wright et al. (1997); Veleva and Ellenbecker (2001);

• Lifecycle impact assessment methodologies (LCIA): i.e., ReCiPe (2009), Eco-indicator 99 (1999), Eco-indicator 95 (1999), CML (2001a, b), BEES, EDIP (2003), Impact (2002), TRACI 2, EPD (2007);

• Indexes series: i.e., global reporting index (GRI), Dow Jones Sustainability World Index (DJSI 2010), and FTSE4Good;

• Software products for LCA and product design: i.e., EIME, SimaPro, and GaBi (LCA software) and SolidWorks (CAD).

• Sustainability oriented methodologies allowing the development of sustainable products, manufacturing systems, and supply networks: i.e., Design for Environment (DfE) (Fiksel 1996; Mascle and Zhao 2008), environmental conscious manufacturing (ECM) (Gungor and Gupta 1999), and GreenSCOR.

As suggested by Guinée (2002), a preliminary selection of the environmental indicators has been performed considering the positioning of the focal point of the indicators in the cause-effect chain that is meant to describe the environmental mechanism from “exchanges” to “endpoints.” In the impact chain, the “exchange” represents the flow of matter and resources between the environment and the techno-sphere. The “endpoint” is the “thing” to be protected, such as trees, rivers, and human health. “Midpoint” refers to all the elements in an environmental mechanism that fall between environmental exchanges and endpoints. An example of an “exchange” is the emission of chlorofluorocarbon (CFC) gases, which causes a depletion of the ozone layer in the stratosphere (midpoint), which results in increased levels of radiation (midpoint) that eventually cause a certain number of people to die from skin cancer (endpoint).

The LCIA and the related impact category indicators could be distinguished into two main approaches, differing in what the indicator is meant to measure along this cause-effect chain.

The first approach, known as problem-oriented, is characterized by category indicators close to the environmental intervention that are driven by the environmental problems. This kind of indicators, called also midpoint, are meant to translate impacts into environmental themes (e.g., global warming, acidification, human toxicity, etc.). The second approach, known as damage-oriented, is characterized by category indicators close to environmental areas of protection. This kind of indicators, called also endpoint indicators, are meant to model the potential environmental damage on value items due to the environmental interventions, translating the environmental impacts into issues of concern such as human health, natural environment, and natural resources.

It is evident that endpoint indicators have a higher level of uncertainty compared to midpoint indicators, since they require the definition of a model to translate emissions into actual damage, enhancing the complexity level of the environmental assessment. In order to avoid the uncertainty introduced by the damage-oriented approach, the SAM assessment model is based on problem-oriented indicators. Although some of the analyzed mentioned LCIA methodologies are damage oriented, it is possible anyhow to extract the midpoint indicators.

The first list derived from literature of the possible environmental indicators to be used in the assessment model is reported in Table 3.1, that also shows the sources of the indicators. Table 3.1 provide a ranking of the indicators based on the application of the Established criteria (the last of those mentioned in the previous section), since each row of the table reports if the indicator is cited in a particular software, LCIA methodology, index system, etc., and then provides the total number of the indicator occurrences. This allows evaluating the academic and industrial consensus in the use of the indicator and in the definition of its calculation formula.

Table 3.1 Indicators versus established criterion

As stated above, the ranking of the environmental indicators listed in Table 3.1 has been carried out applying the selection criterion “established,” as defined in Sect. 3.2.1. Table 3.2 provides the match between the other selection criteria and the indicators, with the exception of the established criterion, already taken into consideration.

Table 3.2 Candidate environmental indicators versus selection criteria

The results of the first selection, visualized in Table 3.2, are summarized hereinafter.

The indicators “Carcinogens Emissions,” “Heavy Metal Emitted to Air,” “Heavy Metal Emitted to Water,” “Pesticides Emissions,” “Respiratory Effects Potential” have been considered not to be balanced and fitting as the “Human Toxicity Potential” and the “Eco toxicity Potential” indicators are meant to assess the same environmental issues with a more comprehensive perspective.

The indicator “Smell Emissions” is not measurable since it is subjected to objective data (chemicals analysis and sensor methodologies), but also to subjective data (nuisance analysis through surveys). The subjective aspect of the indicator implies also that it cannot be based on accessible data so that smell is not achievable.

The literature review shows that actually the calculation methodology of the indicator “Biotic Resource Depletion (biodiversity)” has not yet reached a wide agreement on the academic and the industrial communities. This indicator is difficult to be measured, it is not reliable, there are few available data allowing its calculation and its understandability is negatively affected by the various different assessment methodologies developed in the literature.

“Raw Material Efficiency” indicator encompasses a broad range of concepts and idea about the efficient use of natural resources, but a clear definition of the “material efficiency” is missing so that this indicator is neither measurable nor achievable. Moreover, this indicator is not balanced since it overlaps more structured indicators concerning the efficient use of raw materials (i.e., “Material Recyclability,” “Abiotic Resources Depletion”).

The indicators “Waste Generation” and “Hazardous Waste Production” could be integrated into one indicator evaluating the total amount of waste created by the solution space activities and then distinguishing between hazardous and non-hazardous waste.

“Product Durability” is a qualitative characteristic of the product that is hard to be measured. The prediction of the expected life span of the product in years does not provide a measure of its durability. Moreover, this indicator is not comprehensive since it measures only the product characteristics, ignoring the manufacturing system and the supply chain.

In order to be fully understandable and not to convey misleading information, the “Revenues from Eco-products” indicator requires a precise and shared definition of what is intended to be an “eco-product.” A product is never in absolute eco, rather it is “more green” than a chosen reference product. The necessity to have a reference product introduces a sort of uncertainty in the calculation of this indicator making it not reliable.

The “Presence and quality of the environmental policy,” “Quality and Number of Environmental Reports,” and the “Number of Voluntary Environmental Certifications of the company and its suppliers” indicators are not exploitable, relevant, and influencing change, since they do not properly highlight the existing problems within the company, scarcely enabling decisionmakers to understand which are the necessary corrective actions. Moreover, “Quality of the environmental policy” and “Quality of Environmental Reports” are not measurable in a quantitative and objective way.

Though Azapagic and Perdan (2000) provided a calculation formula for the “Environmental improvements above the compliance levels” indicator, its measurability and understandability are low since it is subjected to the vague definition of “substance that are of general environmental concern but are not legislated.” Moreover, this kind of indicator may lead to expensive corrective action that is not focusing on the core environmental performances of the company.

Combining the results of the analysis performed through the selection criteria summarized in Tables 3.1 and 3.2, the list of the environmental indicators has been obtained and it is presented in Sect. 3.2.3, where the definitions of the indicators and their unit of measure are also provided.

3.2.2.2 Economic Indicators Selection

Achieving economical sustainability means to use resources in an efficient way in order to provide long-term benefits with minimal waste. In other terms, it aims at maximizing the level of quality while minimizing the costs (Global Reporting Initiative 2000–2011). The assessment of the economic sustainability can be referred to different unit of analysis: a single organization, a country, or an industry. At the organizational level, standards and global reporting state that the economical sustainability can be assessed considering the direct economic value (as revenue) and operating costs. In the literature, some contributions are focused on the assessment of economical sustainability of specific industries. In this case, the assessment is based on the measurement of efficiency and profitability levels (Hang et al. 2011). Finally, some researches consider a district (state or country) and base the assessment on national economy and production competitiveness (Corbiere et al. 2011).

According to the aim of the SAM assessment model, the selection of indicators considers the organization level and, in particular, the unit of analysis includes product, production system, and supply chain of a new solution space. In Table 3.3, the list of indicators selected to measure the economic sustainability clustered according to Profitability, Risk Management, Investment (tech. and competences), and Efficiency categories is presented. Indicators are introduced linking them to the selection criteria.

Table 3.3 SAM economical area of concerns and indicators versus selection criteria

3.2.2.3 Social Indicators Selection

Social indicators have not achieved the same level of maturity as environmental ones yet. This can be explained by the focus given during last decades on the environmental dimension of sustainability. The literature of social sustainability assessment methods and indexes shows that lifecycle thinking has also emerged in the social assessment of products, but there are no standards yet, neither methodologies nor indicators. The efforts here are meant to foster the characterization of social impact of products all over their lifecycles, facilitating by the standardization of the life social evaluation methods. The relevance of a reference here investigated is tributary of (1) its frequency in sustainability literature and (2) its date of issue or last update (the nearest the latter, the more relevant is the reference).

Jensen and Remmen (2006) gave insights on lifecycle management and its integration in sustainability dimensions, including social one. GRI (2006a, b) established sustainability reporting guidelines applicable to several organizations. Kruse et al. (2009) proposed a socioeconomic indicators system that has been also applied to a case study demonstrating applicability. Benoît and Bernard (2009) provided more guidance for the establishment of a social lifecycle assessment (S-LCA). Dreyer (2009), Dreyer et al. (2010a, b) attempted to formalize the S-LCA by proposing a methodology that was applied to different case studies.

Investigated literature also includes initiatives that provide comprehensive indicators but they are not applicable at enterprise level such as UN (2001, 2007). Further literature on social sustainability indicators can be found in Jorgensen et al. (2008). The authors presented a review meant to highlight areas of agreement and disagreement in S-LCA. Thus the survey included several initiatives that are not extensively mentioned.

Results of the literature survey are presented in Table 3.4. It can be noticed that several indicators are overlapping. In order to allow a seamless selection process, indicators that measure same aspects are grouped, and then the most relevant indicators depicting these aspects are selected. In some cases, the existing indicators are quite generic, thus proposing new ones related to same aspects is inevitable. The grouping and selection results are illustrated in Table 3.5.

Table 3.4 Candidate social indicators versus selection criteria

Table 3.5 Indicators selection

As mentioned in the beginning of this section, social dimension assessment is not well established yet despite several indicators and methods proposals. Our indicators attempt to fill this gap and to broaden the evaluation scope. In order to fully cover working condition and workforce aspects, three more indicators have been proposed, namely workforce turnover intensity (WTI), multi-skilled operators (MSO), and product social features (PSF).

3.2.3 Indicators List

This section is meant to summarize the list of the selected indicators presenting their definition and their unit of measure. The indicators have been grouped into three subsets considering the sustainability pillars: Environmental indicators, Economic indicators, Social indicators (Tables 3.6, 3.7, 3.8).

Table 3.6 Environmental indicators list

Table 3.7 Economic indicators list

Table 3.8 Social indicators list

3.3 Environmental Indicators Calculation Formulas

The development of the environmental indicators calculation formulas is based on the LCA methodology, using the “Impact Potential” entities defined in Sect. 3.3.1.

Section 3.3.2 addresses the selection of the LCIA to be used for the calculation of the Impact Potential.

Section 3.3.3 is meant to list the lifecycle inventory (LCI) and LCIA databases containing the information needed to calculate the Impact Potentials. Eventually the calculation formulas of the indicators allowing the Assessment of the environmental impact of the solution space are presented.

3.3.1 Development of the Impact Potentials

The environmental interventions that occur during the solution space lifecycle generate flows of matter and energy between technosphere and nature. The LCI analysis lists the flows crossing the system boundaries assigning the LCI results to the impact categories that are the classes representing environmental issues of concern. LCI results provide the starting point for LCIA that is meant to measure the magnitude of the potential environmental impacts of the solution space. The LCIA could be performed through various methodologies that are characterized by a category indicator, a characterization model, and characterization factors. LCIA methodologies translate the input and the output of a process described by the LCI into effects on an environmental impact category measured through the category indicator value. This translation is performed by the characterization factors that are meant to measure the effect on the environment of a single flow relative to a specific basic flow (Guinée 2002).

The specific emission and the specific resources consumed are translated by the characterization factors defined by the LCIA methodologies into specific equivalent impacts within the various impact environmental categories covered by the environmental indicators selected. For instance, using the LCIA methodology IPCC 2007, that is meant to calculate the global warming potential (GWP) of the emitted greenhouse gases, each kilos of CH₄ emitted for each kg of steel extracted is translated into 25 equivalent kg of CO₂ emitted for 1 kg of steel extracted.

The specific equivalent impacts of each substance emitted or resource consumed concerning the same impact category are then summed obtaining what it has been called Impact Potential that is meant to summarize the specific environmental impacts of the solution space activities on a impact category. To sum up, the values of the Potentials can be calculated knowing the LCI results of an activity and considering a specific LCIA methodology. The Potential values and so the indicators values are LCIA methodology dependent. The LCI results could be obtained from direct measures or from LCI databases. Some of the LCI databases (e.g., Ecoinvent) provide also the value of the Potential calculated through various LCIA methodologies.

In order to calculate the environmental category indicator value of an activity performed during the solution space lifecycle (e.g., the extraction of a raw material, the manufacturing process of a component, the transportation of the final product,…), the Potential is multiplied by the “amount” of that activity. The development of the indicators formulas through the concept of Potentials enables the automation of the indicator calculation since the LCA data are grouped in the Potentials. The definitions of the Impact Potentials used in the calculation formulas are presented in Table 3.9.

Table 3.9 Impact potentials definition

3.3.2 Selection of the LCIA Methodology

As stated in Sect. 3.3.1, the Potential values could be calculated by different LCIA methodologies. Literature provides a wide range of available LCIA methodologies that has yet been cited in Sect. 3.2.2.1: ReCiPe 2009, Eco-indicator 99 (1999), Eco-indicator 95 (1999), CML (2001a, b), BEES, EDIP (2003), Impact (2002), TRACI, EPD 2007.

The selection of the LCIA methodology to be applied in the SAM assessment model has been carried out analyzing which of the available LCIA methodologies better address the selected environmental indicators. The map of the indicator covered by the LCIA methodologies has been performed considering the LCIA methods provided by Ecoinvent in order to directly verify the availability of data needed to perform the SAM assessment. Table 3.10 maps the identified environmental indicators covered by the LCIA methodologies included in Ecoinvent; this analysis has been carried out verifying also the coherence between the unit of measure used by Ecoinvent and those described in Sect. 3.3.4. Since the SAM environmental indicators are problem oriented, the damage-oriented LCIA methodologies considered by Ecoinvent (i.e., IMPACT (2002), Eco-indicator 99 (1999), Ecological Scarcity (1997) and (2006), ecosystem damage potential—EDP, and EPS2000) have been excluded in the selection process.

Table 3.10 Match between SAM indicators and ecoinvent LCIA methodologies

In Table 3.10 the “*” means that the indicator is measured with a different unit of measure from those expected in the indicator definition provided in Sect. 3.3.4.

The EDIP methodologies use a different set of unit of measure for two of the SAM indicators addressed, while for the NRD indicator takes into account only the depletion of a limited set of substances. EDIP is the only LCIA method included in Ecoinvent providing the measure of the waste generated by an activity to distinguish the land filling of: bulk waste, hazardous waste, radioactive waste, and slag and ashes.

CML2001 addresses eight of the twelve SAM environmental indicators using also the same unit of measure expected by the indicator definition. Among these eight indicators, the CML method calculates POCP distinguishing different kind of Photochemical Ozone Creation equivalent emissions. In order to obtain the value of the SAM indicator, it is possible to simply sum the different CML contributions concerning the Photochemical Ozone Creation.

The cumulative energy demand methodology is the only one calculating the energy depletion. This methodology distinguishes the depletion of non-renewable energy resources [(i.e., fossil, nuclear, primary forest) and renewable energy resources (i.e., biomass, potential (in barrage water), kinetic (in wind), and solar)].

TRACI covers six of the twelve SAM environmental indicators, but using the same unit of measure expected by the indicator definition for only two of them. Moreover, the methodology analyzes only the ecotoxicity aspect of toxicity.

ReCiPe addresses nine of the twelve SAM environmental indicators but about the acidification it considers only the terrestrial acidification, about the NRD indicator it considers only the metal depletion and the fossil depletion, about toxicity it addresses four toxicity compartments namely human, terrestrial, freshwater, and marine and about land use it considers only agricultural and urban land occupation.

Eventually, the Selected LCI of Ecoinvent covers only two of the twelve SAM environmental indicators even though it is one of the two methodologies addressing the water depletion.

The analysis performed on the LCIA methodologies provided by Ecoinvent shows that CML2001 is the best methodology fitting the SAM environmental indicators even though, in order to cover all the selected indicators, the water depletion of the selected LCI ecoinvent and the waste production (WP) of EDIP2003 have to be added.

CML2001 is a well-established LCIA methodology developed in 1992 and updated along the years obtaining the international agreement. CML2001 methodology is a baseline characterization method, methods that are recommended to be used by Guinée (2002) as the best available LCIA models. Moreover, CML2001 satisfy the selection criteria defined by the ISO relevant standard and the work of the second SETAC-Europe (Society for Environmental Toxicology and Chemistry) Working Group on Impact Assessment. Another advantage of this method is that the characterization factors are available for free allowing the calculation of new or ad hoc Potentials if the LCIA data are not directly available from databases.

3.3.3 LCI and LCIA Databases

The calculation of the environmental indicators needs LCI or LCIA data in order to calculate the Impact Potential mentioned in Sect. 3.3.1. Since the inventory analysis is the most expensive activity of LCA and environmental assessment in general, many databases have been developed in order to gather data about the most commonly used materials and processes that are relevant to the companies. A list of the most frequently used databases by the LCA software is presented in Table 3.11.

Table 3.11 LCI and LCIA databases

The mentioned LCI databases provide data about flows of materials, energy, and emission for a large set of materials and processes. Most of the LCI databases are available for free and in many cases the data are provided in XML format. The use of LCI databases does not completely solve the calculation of the Impact Potentials since the characterization factors of the chosen LCIA methodology are needed too and, as stated in the previous section, they are not always available. In this perspective, the use of databases providing directly LCIA data is preferred since they directly provide the Impact Potential needed to perform the assessment.

3.3.4 Expected Contribution to the Environmental Indicators

The description of the expected contributions to all the indicators calculated on the basis of the Impact Potentials (the whole environment compartment with the exception of Product Recycling Potential indicator) is provided in this section grouping the contributions into the product lifecycle concerned phases.

Extraction: equivalent impact (namely emission, use of resources or waste) caused by the extraction of raw materials constituting the product, its packaging, and the surface treatments (e.g., paint, nickel used in galvanic processes, …).

Material processing: equivalent impact caused by the material processing of the raw materials constituting the product and its packaging.

Part manufacturing: equivalent impact caused by manufacturing operations. Since production processes use auxiliary materials and produce waste materials and scrap components, the equivalent impact occurred during the extraction, the material processing, the manufacturing processes, the transportations (from the suppliers and to the EOL facilities), and the EOL treatments of auxiliary materials, waste materials, and scrap components are also taken into account.

Assembly: equivalent impact caused by assembly operations. Since assembly processes use auxiliary materials and produce scrap assemblies, the equivalent impact occurred during the extraction, the material processing, the transportations (from the suppliers and to the EOL facilities), and the EOL treatments of the auxiliary materials and scrap assemblies are also taken into account.

Product use: equivalent impact caused by the product use. They include both direct impact of the product during its use and indirect equivalent impact due to the energy consumed during the use phase. Since during the use phase consumables are used, the equivalent impact occurred during the extraction, the material processing, the manufacturing processes, the transportations (from the suppliers and to the EOL facilities), and the EOL treatments of the consumables are also taken into account.

Repair: equivalent impact occurred during the extraction, the material processing, the manufacturing processes, the transportations (from the suppliers and to the EOL facilities and customers), and the EOL treatments of the spare parts.

End of life: equivalent impact caused by end of life treatments carried out on the product and its packaging.

Transportation: equivalent impact caused by transportations of raw materials and components from suppliers, transportation of the finished product (product plus packaging) to retailers or customers, and transportations of the finished product to end of life facilities.

The total value of the environmental indicators is obtained summing the contributions of all the lifecycle phases.

3.3.5 Emissions

This section is meant to provide the calculation formulas of the environmental indicators concerning the emissions: the GWP, the Photochemical ozone creation potential (POCP), the eutrophication potential (EP), the stratospheric ozone depletion potential (ODP), the acidification potential (AP), the freshwater aquatic ecotoxicity potential (FAETP), the freshwater sediment ecotoxicity potential (FSETP), the marine aquatic ecotoxicity potential (MAETP), the marine sediment ecotoxicity potential (MSETP), the terrestrial ecotoxicity potential (TETP), and the human toxicity potential (HTP).

3.3.5.1 Global Warming Potential Indicator Calculation Formula

The GWP indicator measures the contribution to the global warming caused by the emission of greenhouse gases in the atmosphere. As suggested by the LCA methodology, the calculation formula addresses both the direct emission of greenhouse gases and the indirect ones caused by the energy consumed by the activity carried out during the lifecycle phases of the product. The greenhouse gas emissions are translated into equivalent kilos of CO₂ emitted using the carbon dioxide as a reference gas. The definition of the GWP calculation formula is provided here (Table 3.12):

Table 3.12 GWP calculation formula

3.3.5.2 Photochemical Ozone Creation Potential Indicator Calculation Formula

The POCP indicator calculates the potential creation of tropospheric ozone (“summer smog” or “photochemical oxidation”) caused by the release of those gases which will become oxidants in the low atmosphere under the action of the solar radiation. As suggested by the LCA methodology, the calculation formula addresses both the direct emission of oxidant gases and the indirect ones caused by the energy consumed by the activity carried out during the lifecycle phases of the product. The oxidant gases emissions are translated into equivalent kg of C₂H₄ emitted using the ethylene as a reference gas. The definition of the POCP calculation formula is provided here, by offering a substitution table that allows to derive the POCP calculus from the previous described GWP formula, given its similarity due to the application of the same Impact Potentials method (Table 3.13).

Table 3.13 POCP calculation formula through substitution

3.3.5.3 Eutrophication Potential Indicator Calculation Formula

The EP indicator measures the contribution to the water eutrophication (enrichment in nutritive elements) of lakes and marine waters caused by the release of polluting substances in the water. As suggested by the LCA methodology, the calculation formula addresses both the direct emission of eutrophicating substances and the indirect ones caused by the energy consumed by the activity carried out during the lifecycle phases of the product. The eutrophicating substances emissions are translated into equivalent kg of PO₄ ³⁻ emitted using the phosphates as reference substances. The definition of the EP calculation formula is provided here, by offering a substitution table that allows to derive the EP calculus from the previous described GWP formula, given its similarity due to the application of the same Impact Potentials method (Table 3.14).

Table 3.14 EP calculation formula through substitution

3.3.5.4 Stratospheric Ozone Depletion Potential Indicator Calculation Formula

The ODP indicator measures the contribution to the depletion of the stratospheric ozone layer caused by the emission of ozone depleting gases. As suggested by the LCA methodology, the calculation formula addresses both the direct emission of ozone depleting gases and the indirect ones caused by the energy consumed by the activity carried out during the lifecycle phases of the product. The ozone depleting gases emissions are translated into equivalent kg of CFC-11 emitted using the trichlorofluoromethane as reference substance. The definition of the ODP calculation formula is provided here, by offering a substitution table that allows to derive the ODP calculus from the previous described GWP formula, given its similarity due to the application of the same Impact Potentials method (Table 3.15).

Table 3.15 ODP calculation formula through substitution

3.3.5.5 Acidification Potential Indicator Calculation Formula

The AP indicator measures the contribution to the acidification caused by acidification gases emitted in the atmosphere. As suggested by the LCA methodology, the calculation formula addresses both the direct emission of acidification gases and the indirect ones caused by the energy consumed by the activity carried out during the lifecycle phases of the product. The acidification gases emissions are translated into equivalent kg of SO₂ emitted using the sulfur dioxide as reference substances. The definition of the EP calculation formula is provided here, by offering a substitution table that allows to derive the EP calculus from the previous described GWP formula, given its similarity due to the application of the same Impact Potentials method (Table 3.16).

Table 3.16 AP calculation formula through substitution

3.3.5.6 Freshwater Aquatic Eco Toxicity Potential Indicator Calculation Formula

The FAETP measures the relative impact of toxic substances on the freshwater aquatic environment due to the emissions to environmental compartments air, freshwater, seawater, agricultural, and industrial soil. As suggested by the LCA methodology, the calculation formula addresses both the direct emission of toxic substances and the indirect ones caused by the energy consumed by the activity carried out during the lifecycle phases of the product. The toxic substances emissions are translated into equivalent kg of 1,4-DCB emitted using the 1,4 dichlorobenzene as reference substance. The definition of the FAETP calculation formula is provided here, by offering a substitution table that allows to derive the FAETP calculus from the previous described GWP formula, given its similarity due to the application of the same Impact Potentials method (Table 3.17).

Table 3.17 FAETP calculation formula through substitution

3.3.5.7 Marine Aquatic Eco Toxicity Potential Indicator Calculation Formula

The MAETP measures the relative impact of toxic substances on the marine aquatic environment due to the emissions to environmental compartments air, freshwater, seawater, agricultural, and industrial soil. As suggested by the LCA methodology, the calculation formula addresses both the direct emission of toxic substances and the indirect ones caused by the energy consumed by the activity carried out during the lifecycle phases of the product. The toxic substances emissions are translated into equivalent kg of 1,4-DCB emitted using the 1,4 dichlorobenzene as reference substance. The definition of the MAETP calculation formula is provided here, by offering a substitution table that allows to derive the MAETP calculus from the previous described GWP formula, given its similarity due to the application of the same Impact Potentials method (Table 3.18).

Table 3.18 MAETP calculation formula through substitution

3.3.5.8 Freshwater Sediment Eco Toxicity Potential Indicator Calculation Formula

The FSETP measures the relative impact of toxic substances on the freshwater sediment environment due to the emissions to environmental compartments air, freshwater, seawater, agricultural, and industrial soil. As suggested by the LCA methodology, the calculation formula addresses both the direct emission of toxic substances and the indirect ones caused by the energy consumed by the activity carried out during the lifecycle phases of the product. The toxic substances emissions are translated into equivalent kg of 1,4-DCB emitted using the 1,4 dichlorobenzene as reference substance. The definition of the FSETP calculation formula is provided here, by offering a substitution table that allows to derive the FSETP calculus from the previous described GWP formula, given its similarity due to the application of the same Impact Potentials method (Table 3.19).

Table 3.19 FSETP calculation formula through substitution

3.3.5.9 Marine Sediment Eco Toxicity Potential Indicator Calculation Formula

The MSETP measures the relative impact of toxic substances on the marine sediment environment due to the emissions to environmental compartments air, freshwater, seawater, agricultural, and industrial soil. As suggested by the LCA methodology, the calculation formula addresses both the direct emission of toxic substances and the indirect ones caused by the energy consumed by the activity carried out during the lifecycle phases of the product. The toxic substances emissions are translated into equivalent kg of 1,4-DCB emitted using the 1,4 dichlorobenzene as reference substance. The definition of the MSETP calculation formula is provided here, by offering a substitution table that allows to derive the MSETP calculus from the previous described GWP formula, given its similarity due to the application of the same Impact Potentials method (Table 3.20).

Table 3.20 MSETP calculation formula through substitution

3.3.5.10 Terrestrial Eco Toxicity Potential Indicator Calculation Formula

The TETP measures the relative impact of toxic substances on the terrestrial environment due to the emissions to environmental compartments air, freshwater, seawater, agricultural, and industrial soil. As suggested by the LCA methodology, the calculation formula addresses both the direct emission of toxic substances and the indirect ones caused by the energy consumed by the activity carried out during the lifecycle phases of the product. The toxic substances emissions are translated into equivalent kg of 1,4-DCB emitted using the 1,4 dichlorobenzene as reference substance. The definition of the TETP calculation formula is provided here, by offering a substitution table that allows to derive the TETP calculus from the previous described GWP formula, given its similarity due to the application of the same Impact Potentials method (Table 3.21).

Table 3.21 TETP calculation formula through substitution

3.3.5.11 Human Toxicity Potential Indicator Calculation Formula

The HTP measures the relative impact of toxic substances on human beings related to the to the emissions in environmental compartments, namely air, freshwater, seawater, agricultural, and industrial soil. As suggested by the LCA methodology, the calculation formula addresses both the direct emission of toxic substances and the indirect ones caused by the energy consumed by the activity carried out during the lifecycle phases of the product. The toxic substances emissions are translated into equivalent kg of 1,4-DCB emitted using the 1,4 dichlorobenzene as reference substance. The definition of the HTP calculation formula is provided here, by offering a substitution table that allows to derive the HTP calculus from the previous described GWP formula, given its similarity due to the application of the same Impact Potentials method (Table 3.22).

Table 3.22 HTP calculation formula through substitution

3.3.6 Use of Resources

This section is meant to provide the calculation formulas of the environmental indicators concerning the use of resources: the natural resource depletion (NRD), the land use (LU), the water depletion (WD), the energy depletion (ED).

The description of the expected contributions to the use of resources indicators is provided in this section grouping the contributions into the product lifecycle phases concerned.

3.3.6.1 Natural Resources Depletion Indicator Calculation Formula

The NRD indicator measures the depletion of non-renewable abiotic natural resources (i.e., fossil and mineral resources) as the fraction of the resource reserve used for a single unit out of the solution space weighted by the fraction of the resource reserve that is extracted in the world in one year. The natural resources depleted are translated into equivalent depleted kilos of Sb using the antimony as a reference substance. The definition of the NRD calculation formula is provided here, by offering a substitution table that allows to derive the NRD calculus from the previous described GWP formula, given its similarity due to the application of the same Impact Potentials method (Table 3.23).

Table 3.23 NRD calculation formula through substitution

3.3.6.2 Land Use Indicator Calculation Formula

The LU indicator measures the land occupation caused by the production and the delivery of one unit of product belonging to the solution space. The definition of the LU calculation formula is provided here, by offering a substitution table that allows to derive the LU calculus from the previous described GWP formula, given its similarity due to the application of the same Impact Potentials method (Table 3.24).

Table 3.24 LU calculation formula through substitution

3.3.6.3 Water Depletion Indicator Calculation Formula

The WD indicator measures the water of any quality (drinkable, industrial, etc.) consumed during the whole lifecycle of the product. Water used in a closed loop processes are not taken into account. The definition of the WD calculation formula is provided here, by offering a substitution table that allows to derive the WD calculus from the previous described GWP formula, given its similarity due to the application of the same Impact Potentials method (Table 3.25).

Table 3.25 WD calculation formula through substitution

3.3.6.4 Energy Depletion Indicator Calculation Formula

The ED indicator measures the energy consumed during the whole lifecycle of the product distinguishing between renewable and non-renewable sources. The definition of the ED calculation formula is provided here, by offering a substitution table that allows to derive the ED calculus from the previous described GWP formula, given its similarity due to the application of the same Impact Potentials method (Table 3.26).

Table 3.26 ED calculation formula through substitution

Moreover, in addition to the usual substitution process, it is necessary to remove an element from the use phase concerning the direct consumption that is already computed. The use phase part of the formula results in the following (Table 3.27):

Table 3.27 ED use phase calculation formula

3.3.7 Waste

This section is meant to provide the calculation formulas of the environmental indicators concerning the waste: the WP and the Product Recycling Potential (PRP).

The description of the expected contributions to the WP indicator is provided in this section grouping the contributions into the product lifecycle phases concerned.

3.3.7.1 Waste Production Indicator Calculation Formula

The WP indicator calculates the quantity of waste produced during the whole lifecycle of the product. The definition of the WP calculation formula is provided here, by offering a substitution table that allows to derive the WP calculus from the previous described GWP formula, given its similarity due to the application of the same Impact Potentials method (Table 3.28).

Table 3.28 WP calculation formula through substitution

3.3.7.2 Product Recycling Potential Indicator Calculation Formula

The PRP indicator calculates the percentage in weight of the product that could be recycled using the current best recycling techniques. The only lifecycle phase affecting the PRP indicator is the End of life. The definition of the PRP calculation formula is provided here and is quite different from the other environmental indicators since, for its specific nature, it does not fit in the Impact Potentials methodology approach (Table 3.29).

Table 3.29 PRP calculation formula

3.4 Economic Indicators Calculation Formulas

In this sections the economical indicators are presented. They are subdivided into the identified contributions of each lifecycle phase of the product. For each indicator its scope of measurement, lifecycle phases contributions, and final formula are delivered.

3.4.1 Efficiency

3.4.1.1 Unitary Production Variable Cost Indicator Calculation Formula

The unitary production variable cost (UPVC) is conceived to assets the unitary production costs of the customizable product in order to evaluate the level of efficiency of the designed solution space.

For the appraisement of this indicator the whole solution space has to be taken into account: such as the components materials costs, the production system consumption of energy, the cost of labor, and the cost paid to suppliers.

Following is the description of the expected contributions to the UPVC value subdivided into the lifecycle phases.

Extraction: in the extraction phase the expected contributions to the UPVC value are from both costs paid to suppliers who perform extraction of different component materials (cumulating costs which different suppliers face in order to extract components materials of the solution space product plus the transportation cost) and costs of the same processes performed by the company itself (cost of energy consumption and operators who operates on extraction of materials of components).

Material processing: in the material processing phase the expected contributions to the UPVC value are from costs which are both paid to suppliers (cost of processing which is undertaken by supplier plus the transportation cost) and costs that the company itself undertakes in order to perform this process (costs of energy and cost of labor).

Part manufacturing: in the part manufacturing phase the expected contributions to the UPVC value are from both costs paid to suppliers who manufactured the part (purchasing costs of components from suppliers, transportation cost is also included) and from costs related to processes preformed by the company itself (cost of energy consumption and cost of operators who operates on the manufacturing of parts).

Assembly: in the assembly phase the expected contribution to the UPVC value comes from both cost paid to suppliers who assemble product variants (purchasing costs of assembly from suppliers, transportation cost is also included) and from the company itself when it performs this processes (cost of energy consumption and cost of operators who assembles product variants).

Transportation: in the transportation phase the expected contribution to the UPVC value comes from only in house production in case transportation is needed between production plants placed on different locations. In case of outsourcing phases, the purchasing cost includes the transportation costs and therefore it does not affect the transportation phase.

The total value of the UPVC indicator is obtained summing the contributions of all the lifecycle phases and its calculation formula is provided here (Table 3.30).

Table 3.30 UPVC calculation formula

3.4.1.2 Production Lead Time Indicator Calculation Formula

The PLT indicator measures the average time required to manufacture a product belonging to the solution space following the expected mix distribution. The PLT considers only the production activities performed in the last manufacturing step of the product which, in a mass customized context, typically coincide with the processes carried out by the company. The PLT includes the processing time, the queue time, the setup time, the move time, the idle time, and the inspection time, assessing the time passed from the start of the item production to its end. Calculation of the PLT for each product of the expected product mix is usually obtained by simulating the manufacturing system behavior.

However, a very simple formula is provided below to be used for first glance evaluation. The formula has been structured similarly to the other indicators in order to map the design activities affecting the PLT value, even though the decisions taken in the design of the product and the manufacturing system are not the only factors influencing the PLT. Some other factors as queue time and idle time are not easy to be foreseen during the design phase since they derive from a multiproduct manufacturing system.

The lifecycle phases expected to contribute to the PLT indicator are the Extraction, the Material Processing (when this phases are potentially carried out in the last production step), the Part manufacturing, and the Assembly phases (Table 3.31).

Table 3.31 PLT calculation formula

3.4.1.3 Variability of Production Lead Time Indicator Calculation Formula

The variability of production lead time (VPLT) indicator measures how much the production lead time of products belonging to the expected product mix can differ from the PLT mean value. In other words, it is the coefficient of variation.

The VPLT calculation formula is provided below. The design activities affecting the VPLT value are the same of the PLT indicator and the data needed to calculate the VPLT are usually obtained through the manufacturing system simulation (Table 3.32).

Table 3.32 VPLT calculation formula

3.4.1.4 Value Added Time Indicator Calculation Formula

The value added time (VAT) indicator measures the average percentage of the production time spent for operations that increase the value of the product. The VAT value is calculated as the ratio of the processing time spent while performing manufacturing and assembly operations (the VAT) and the total production time that includes the processing time, the move time, the setup time, and the queue time.

As presented in the VAT calculation formula provided below, the numerator of the ratio is the sum of the processing time of all the components and assemblies constituting the expected product mix and the denominator of the formula is the sum of the processing time, the move time, the setup time, and the queue time of all the components and assemblies constituting the expected product mix. The data concerning the processing time, the move time, the setup time, and the queue time of all the components and assemblies are usually obtained through manufacturing system simulation. Similar to the PLT indicator, the formula has been structured in order to map the design activities affecting the VAT value even though the decisions taken in the design of the product and the manufacturing system are not the only factors influencing the VAT.

The lifecycle phases expected to contribute to the VAT indicator are the Extraction, the Material Processing, the Part manufacturing, and the Assembly phases though the calculated value is overall (Table 3.33).

Table 3.33 VAT calculation formula

3.4.1.5 Throughput Rate Indicator Calculation Formula

The throughput rate (TR) is defined as the average product production rate of the system. This measure is expressed as units produced per time period. The design of both the product and the production system influences the throughput rate, but the mechanics which cause the final result cannot be easily quantified during the design phase. For example, phenomena such as queues in front of production resources, effect of the scheduling, capacity of buffers cannot be deduced analytically. All these phenomena are typical of a multiproduct system with a nonlinear production flow. In order to calculate this indicator, it is thus not possible to develop a formula only through analytical means and the value has to be derived through production simulation of the expected mix.

3.4.1.6 Capacity Utilization Rate Indicator Calculation Formula

This indicator is a measure of how much the system potentialities are used and it is calculated as the ratio of the effective capacity and the ideal capacity. Effective capacity is the capacity a firm expects to achieve given the current operating constraints (product mix, methods of scheduling, maintenance and standards of quality, absenteeism, shortages, etc.). On the other hand, ideal capacity is the capacity that could be achieved when none of the above-mentioned factors influences the system. It is thus the maximum theoretical output of a system in a given period. Given these definitions it is possible to measure the two capacity values as throughput rates considering two different production scenarios.

The resulting value is a percentage that gives an idea about how the production system is used and what is the combined effect of different causes of production efficiency losses, thus providing the company with an efficiency measurement.

According to what has been explained for the TR indicator, also in this case it is possible to quantify the values only using simulation. In particular, the ideal capacity is the TR when the systems run without scraps and failures the product mix being equal, while the effective capacity is the same as the TR indicators.

The CUR calculation formula is provided here (Table 3.34).

Table 3.34 CUR calculation formula

3.4.2 Profitability

3.4.2.1 Unitary Expected Gross Profit Indicator Calculation Formula

The unitary expected gross profit (UEGP) is conceived to assess the level of profitability of the designed product solution space. This indicator measures the difference between the unitary revenues obtained by the yearly product sales (calculated on the expected volume and product mix) and the unitary related costs, before deducting administrative and selling expenses, taxation, and interest payments.

Since the UEGP calculation uses the UPVC indicator, the design activities affecting the UEGP are the same of the UPVC and the same is to the expected contribution of the impacts over the lifecycle phases (see Sect. 3.4.1.1). The UEGP calculation formula is provided here (Table 3.35).

Table 3.35 UEGP calculation formula

3.4.2.2 Product Lifecycle Cost Indicator Calculation Formula

The product lifecycle cost (PLC) aims to assess the level of profitability of the designed product solution space by taking into account the whole set of costs the customer has to face during the product lifecycle. This indicator utilizes the expected product price, maintenance costs, repair costs, and end of life costs.

The expected contributions to the PLC value are here subdivided into the product lifecycle phases.

Product use: In the product use phase, the expected contributions to the PLC value are the cost of energy which the product will dissipate and the consumables it will consume during its use phase.

Repair: In repair phase the expected contributions to the PLC value are the cost of spare parts (only those which are not included in warranty or for which warranty has expired) and the cost of technical assistance services which are expected to be required by the product.

End of life: In end of life phase, the expected contributions to the PLC value are costs of product disposal.

The total value of the PLC indicator is obtained summing the contributions of all the lifecycle phases and its calculation formula is provided in Table 3.36.

Table 3.36 PLC calculation formula

3.4.3 Investment in Technologies and Competencies

3.4.3.1 Research and Development Investment Intensity Indicator Calculation Formula

The research and development investment intensity (RDII) indicator measures the research and development investments made by the company and its suppliers, allocating these investments on the solution space and along the whole lifecycle of the product. The R&D investment allows the business of company and supply chain members to last and evolve in a long-term perspective.

The RDII calculation formula is presented in Table 3.37. For each lifecycle phase the first contribution described is about the company, while the next ones are about the suppliers. In each lifecycle phase, the investments made by the company for that specific phase are allocated to the solution space and divided by the number of product expected to be produced in the product mix in order to obtain a unitary value. The suppliers' contributions are indeed already unitary and allocated to the solution space. In each lifecycle phase, the R&D investments made by each supplier are weighted through the ratio of the cost of the item or service provided and the sales turnover of the supplier. Then the contribution of each item is summed considering its frequency within the solution space. The suppliers’ contributions are structured so that the terms concerning the R&D investments allocated to each item provided could be obtained through the calculation provided in Table 3.37 or through data coming from database that could be developed in the future.

Table 3.37 RDII calculation formula

The expected contributions to the RDII indicators are presented in the following for each lifecycle phase.

Extraction: Average yearly unitary R&D investments made by the company in extraction activities allocated on the solution space and the average yearly R&D investments made by the suppliers allocated on the provided raw materials.

Material processing: Average yearly unitary R&D investments made by the company in material processing activities allocated on the solution space and the average yearly R&D investments made by the suppliers allocated on the material processing provided.

Part manufacturing: Average yearly unitary R&D investments made by the company in manufacturing activities allocated on the solution space including, when these activities are directly carried out by the company, the extraction, the material processing, the EOL, and the transportation of auxiliary and waste materials produced by the manufacturing activities; average yearly R&D investments made by the suppliers allocated on the components provided. Average yearly R&D investments made by the suppliers in the extraction, the material processing, the EOL, and the transportation allocated on the provided auxiliary and waste materials.

Assembly: Average yearly unitary R&D investments made by the company in assembly activities allocated on the solution space including, when these activities are directly carried out by the company, the extraction, the material processing, the EOL, and the transportation of auxiliary materials produced by the manufacturing activities; average yearly R&D investments made by the suppliers allocated on the assembly provided. Average yearly R&D investments made by the suppliers in the extraction, the material processing, the EOL, and the transportation allocated on the provided auxiliary materials.

Product use: Average yearly unitary R&D investments made by the company in product features (e.g., a new material, the power dissipated during its functioning) allocated on the solution space including the R&D investments in the extraction, the material processing, the manufacturing, the EOL, and the transportations of consumables when these activities are directly carried out by the company. Average yearly R&D investments made by the suppliers in the extraction, the material processing, the manufacturing, the EOL, and the transportations allocated on the provided consumables.

Repair: Average yearly unitary R&D investments made by the company in repair activities allocated on the solution space including the investments made in the extraction, the material processing, the manufacturing, the EOL, and the transportations of spare parts when these activities are directly carried out by the company. Average yearly R&D investments made by the suppliers in the extraction, the material processing, the manufacturing, the assembly, the EOL, and the transportation allocated on the provided spare parts.

End of life: Average yearly unitary R&D investments made by the company in end of life treatments of the product allocated on the solution space and average yearly R&D investments made by the EOL facilities allocated on the provided EOL treatments.

Transportation: Average yearly unitary R&D investments made by the company in transportation activities allocated on the solution space. Average yearly R&D investments made by the suppliers allocated on the transportation provided. In this phase are considered all the transportation carried out on components, assemblies, and final products: transportations between the company sites, transportations from the suppliers, transportations to customers and retailers, transportations to EOL facilities.

The total value of the RDII indicator is obtained summing the contributions of all the lifecycle phases and its calculation formula is provided in Table 3.37.

3.4.4 Risk Management

3.4.4.1 Supply Risk Indicator Calculation Formula

The supply risk (SR) indicator is a quantitative indicator based on qualitative evaluations measuring the risk associated to the provision of items (raw materials, components, modules, parts, or final products) or services by the suppliers belonging to the supply chain defined by the solution space. This indicator is based on the two different factors:

• the provided resource criticality which is a qualitative measure of the item availability on the market, evaluated considering the number of possible alternative suppliers, and the ease in changing supplier, evaluated considering the setup time of a new supplier;

• the supplier risk which is a qualitative measure of the financial reliability of the supplier that provides the item.

Each lifecycle phase is characterized by a specific criticality depending on the item or service provided (e.g., material, components, assembly, etc.):

Extraction: in this phase the risk related to the purchasing of raw materials constituting the product, its surface treatments, and its packaging is assessed. The material criticality is here evaluated.

Material processing: in this phase the risk related to the purchasing of material processing carried out on the raw materials constituting the product, its surface treatments, and its packaging is assessed. The material processing criticality is here evaluated.

Part manufacturing: in this phase the risk related to the purchasing of components and auxiliary materials is assessed. The component criticality, the auxiliary material criticality, and the material processing concerning auxiliary materials criticality are here evaluated.

Assembly: in this phase the risk related to the purchasing of assemblies and auxiliary materials is assessed. The assembly criticality, the auxiliary material criticality and the material processing concerning auxiliary materials criticality are here evaluated.

The total value of the SR indicator is obtained by combining the contributions of all the lifecycle phases, whose calculation formulas are provided in Table 3.38, through the following formula:

$$ {\text{SR }} = { 1} - \left[ {\left( { 1- {\text{SR}}_{\text{ext}} } \right) \, \times \, \left( { 1- {\text{SR}}_{\text{mp}} } \right) \, \times \, \left( { 1- {\text{SR}}_{\text{pm}} } \right) \, \times \, \left( { 1- {\text{SR}}_{\text{as}} } \right)} \right] $$

Table 3.38 SR calculation formula

3.5 Social Indicators Calculation Formulas

Since the social pillar of sustainability did not get as much attention as environmental and economic pillars, the development of social indicators formulas starts almost from scratch for the majority of the indicators. This section is meant to provide for each indicator the scope of measurement, the general description of the formula and, whenever possible, the contributions to the indicator value grouped into the product lifecycle phases. The calculation formulas and the description of the acronyms, indexes, and terms used in the formula are also provided.

3.5.1 Working Condition and Workforce

3.5.1.1 Injury Intensity Indicator Calculation Formula

This indicator is meant to evaluate the average number of injuries per produced unit within the solution space considering the contribution of all actors involved in the production in different lifecycle phases.

For each lifecycle phase there are two contributions: the first is due to the part of activities carried out by the company, while the next one considers the contribution from suppliers who carry out part of activities belonging to the same phase. Since the number of injuries is usually measured at the company level, in order to allocate the number of injuries to the solution space, the turnover is used as allocation driver. In each lifecycle phase, the injuries occurred in each supplier are weighted through the ratio of the cost of the item or service provided and the sales turnover of the supplier. For the company, the number of injuries is multiplied for the ratio of the turnover generated by the solution space and the total turnover of the company. The value due to the company is then divided by the yearly production volume to get the unitary value (the suppliers' contributions are indeed already unitary and allocated to the solution space). Then the contributions of each item are summed considering their frequency within the solution space. The suppliers’ contributions are structured so that the terms concerning the injuries allocated to each item can be provided directly in the calculation formula of Table 3.39 or, in the future, retrieved from database whenever available.

Table 3.39 II calculation formula through substitution

The expected contributions to the injury intensity (II) indicator are presented below. The II indicator is the first of a subset of the social indicators related to the intensity of different issues (including also Safety Expenditure Intensity, WTI, Staff Development Investments Intensity, and Charitable Contributions Intensity) and therefore the following considerations can be extended to those indicators.

Extraction: average yearly unitary injuries occurred in the company during the extraction activities allocated on the solution space and the average yearly injuries occurred in the suppliers allocated on the provided raw materials.

Material processing: average yearly unitary injuries occurred in the company during material processing activities allocated on the solution space and the average yearly injuries occurred in the suppliers allocated on the material processing provided.

Part manufacturing: average yearly unitary injuries occurred in the company during manufacturing activities allocated on the solution space including, when these activities are directly carried out by the company, the extraction, the material processing, the EOL, and the transportation of auxiliary and waste materials produced by the manufacturing activities; average yearly injuries occurred in the suppliers allocated on the components provided; average yearly injuries occurred in the suppliers during the extraction, the material processing, the EOL, and the transportation allocated on the provided auxiliary and waste materials.

Assembly: average yearly unitary injuries occurred in the company during assembly activities allocated on the solution space including, when these activities are directly carried out by the company, the extraction, the material processing, the EOL, and the transportation of auxiliary materials needed by the assembly activities; average yearly injuries occurred in the suppliers allocated on the assembly provided; average yearly injuries occurred in the suppliers during the extraction, the material processing, the EOL, and the transportation allocated on the provided auxiliary materials.

Product use: average yearly unitary injuries occurred in the company during the extraction, the material processing, the manufacturing, the EOL, and the transportations of consumables when these activities are directly carried out by the company; average yearly injuries occurred in the suppliers during the extraction, the material processing, the manufacturing, the EOL, and the transportations allocated on the provided consumables.

Repair: average yearly unitary injuries occurred in the company during repair activities allocated on the solution space including the injuries occurred during the extraction, the material processing, the manufacturing, the EOL, and the transportations of spare parts when these activities are directly carried out by the company; average yearly injuries occurred in the suppliers during the extraction, the material processing, the manufacturing, the assembly, the EOL, and the transportation allocated on the provided spare parts.

End of life: average yearly unitary injuries occurred in the company during end of life treatments of the product allocated on the solution space; average yearly injuries occurred in the EOL facilities allocated on the provided EOL treatments.

Transportation: average yearly unitary injuries occurred in the company during transportation activities allocated on the solution space; average yearly injuries occurred in the suppliers allocated on the transportation provided. In this phase, all the transportations carried out on components, assemblies, and final products are considered: transportations between the company sites, transportations from the suppliers, transportations to customers and retailers, transportations to EOL facilities.

The total value of the II indicator is obtained summing the contributions of all the lifecycle phases. The definition of the II calculation formula is provided here, by offering a substitution table that allows to derive the II calculus from the previous described RDII formula, given its similarity due to the application of the same intensity method.

3.5.1.2 Safety Expenditure Intensity (II) Indicator Calculation Formula

This indicator is meant to measure the average unitary expense in safety issues considering the contribution of all actors involved in the production in different lifecycle phases.

For each lifecycle phase, the first contribution described is about the company, while the next ones are about the suppliers. In each lifecycle phase, the safety expenditures made by the company for that specific phase are allocated to the solution space and divided by the number of product expected to be produced in the product mix in order to obtain a unitary value. The allocation driver is the ratio of the turnover generated by the solution space and the total turnover of the company. The suppliers' contributions are indeed already unitary and allocated to the solution space. In each lifecycle phase, the safety expenditures made by each supplier are weighted through the ratio of the cost of the item or service provided and the sales turnover of the supplier. Then the contributions of each item are summed considering its frequency within the solution space. The suppliers’ contributions are structured so that the terms concerning the safety expenditures allocated to each item can be provided directly in the calculation formula of Table 3.40 or, in the future, retrieved from database whenever available.

Table 3.40 SEI calculation formula through substitution

The expected contributions to the SEI indicators are the same as for the II indicator as described in Sect. 3.5.1.1. The definition of the SEI calculation formula is provided here, by offering a substitution table that allows to derive the SEI calculus from the previous described RDII formula, given its similarity due to the application of the same intensity method.

3.5.1.3 Employment Opportunity Indicator Calculation Formula

The employment opportunity (EO) indicator measures the percentage of the new employment opportunities created by the introduction of the solution space considering the contributions of the company only. The EO calculation formula is provided here (Table 3.41).

Table 3.41 EO calculation formula

3.5.1.4 Workforce Turnover Intensity Indicator Calculation Formula

Social sustainability is intended to track stakeholders and one of them is workforce. Evaluation of the level of workforce satisfaction with their job results into development of an indicator called WTI. This indicator targets to evaluate rate of solution space workforces who leave the company considering all the supply chain actors (company and suppliers) along the product lifecycle.

For each lifecycle phase, the first contribution described is about the company, while the next ones are about the suppliers. In each lifecycle phase the number of employees working in that specific phase that are leaving the company are allocated to the solution space and divided by the number of product expected to be produced in the product mix in order to obtain a unitary value. The allocation driver is the ratio of the turnover generated by the solution space and the total turnover of the company. The suppliers’ contributions are indeed already unitary and allocated to the solution space. In each lifecycle phase, the employees leaving the supplier are weighted through the ratio of the cost of the item or service provided and the sales turnover of the supplier. Then the contributions of each item are summed considering its frequency within the solution space. The suppliers’ contributions are structured so that the terms concerning the employees leaving the supplier allocated to each item can be provided directly in the calculation formula of Table 3.42 or, in the future, retrieved from database whenever available.

Table 3.42 WTI calculation formula through substitution

The expected contributions to the WTI indicators are the same as for the II indicator as described in Sect. 3.5.1.1. The definition of the WTI calculation formula is provided here, by offering a substitution table that allows to derive the WTI calculus from the previous described RDII formula, given its similarity due to the application of the same intensity method.

3.5.1.5 Multi-Skilled Operators Indicator Calculation Formula

This indicator is used as a proxy to measure how flexible the workforce is calculating the ratio of multi-skilled operators working within the solution space and the total number of operators working within the solution space. An operator is multi-skilled when he/she is able to perform more than one operation. In case the operator works in different department, he/she is considered only once in the department where he/she spends most of the time and he/she is considered to be multi-skilled even though in this department he/she is able to perform only one operation. The workforce flexibility is a plus in a mass customized environment since it allows operators to be moved in different areas of the production system depending on the workload of a specific moment that could be different in different areas as a consequence of the multiproduct context. This indicator is the sum of the values calculated for each production phase (extraction, material processing, manufacturing, assembly) as explained in more detail in what follows.

This section is meant to provide the description of the expected contributions to the MSO value from the different lifecycle phases.

Extraction: in the extraction phase the MSO is calculated as the ratio of the number of operators who are able to perform more than one extraction operation and the total number of operators working in the extraction department of the company.

Material processing: in the material processing phase the MSO is calculated as the ratio of the number of operators who are able to perform more than one material processing activity and the total number of operators working in the material processing department of the company.

Part Manufacturing: in the manufacturing phase the MSO is calculated as the ratio of the number of operators who are able to perform more than one manufacturing operation.

Assembly: in the assembly phase the MSO is calculated as the ratio of the number of operators who are able to perform more than one assembly operation.

The MSO calculation formula is provided here (Table 3.43).

Table 3.43 MSO calculation formula

3.5.1.6 Staff Development Investment Intensity Indicator Calculation Formula

The staff development investment intensity (SDII) indicator measures the staff development investments made by the company and its suppliers for each unit of product, allocating these investments on the solution space and along the whole lifecycle of the product. The staff development investments are meant to train up labors and employees in order to enhance the workforce competencies.

For each lifecycle phase, the first contribution described is about the company, while the next ones are about the suppliers. In each lifecycle phase, the investments made by the company for that specific phase are allocated to the solution space and divided by the number of product expected to be produced in the product mix in order to obtain a unitary value. The allocation driver is the ratio of the turnover generated by the solution space and the total turnover of the company. The suppliers' contributions are indeed already unitary and allocated to the solution space. In each lifecycle phase, the staff development investments made by each supplier are weighted through the ratio of the cost of the item or service provided and the sales turnover of the supplier. Then the contributions of each item are summed considering its frequency within the solution space. The suppliers’ contributions are structured so that the terms concerning the staff development investments allocated to each item can be provided directly in the calculation formula of Table 3.44 or, in the future, retrieved from database whenever available.

Table 3.44 SDII calculation formula through substitution

The expected contributions to the SDII indicators are the same as for the II indicator as described in Sect. 3.5.1.1. The definition of the SDII calculation formula is provided here, by offering a substitution table that allows to derive the SDII calculus from the previous described RDII formula, given its similarity due to the application of the same intensity method.

3.5.1.7 Income Level Indicator Calculation Formula

The income level (IL) measures are meant to compare the employees income of the solution space with an average yearly income per person taken as reference considering the weighted contribution of the company and its suppliers (the supply chain members) along the whole lifecycle of the product. For each supply chain member, the IL is measured as the ratio of the average yearly employee income and the average yearly income per person in the country where the supply chain member is placed. The employees included in this evaluation are from labors to middle management.

For each lifecycle phase, the IL of each supply chain member contributing to this phase is assessed. Then the contribution of each supply chain member is weighted: the suppliers' contribution through the ratio of the unitary costs paid to the supplier and the sum of the unitary purchasing expenditures and the unitary variable cost incurred by the company; the company contribution through the ratio of the unitary variable costs afforded by the company and the sum of the unitary purchasing expenditures and the unitary variable cost incurred by the company. The weighted contributions are then summed along the product lifecycle phases in order to obtain the total value of the IL indicator.

The expected contributions to the IL value are grouped in the following into the product lifecycle phases.

Extraction: weighted IL of company and suppliers performing extraction activities.

Material processing: weighted IL of company and suppliers performing material processing activities.

Part manufacturing: weighted IL of company and suppliers performing manufacturing activities.

Assembly: weighted IL of company and suppliers performing assembly activities.

Use: weighted IL of company and suppliers manufacturing consumables.

Repair: weighted IL of company and suppliers performing repair activities.

End of life: weighted IL of company and suppliers performing end of life treatments.

Transportation: weighted IL of company and suppliers performing transportations. Since the costs paid to the suppliers in the other lifecycle phases usually include the transportation costs, here are considered the transportation costs paid to transportation suppliers for inter sites movements and the unitary variable costs of transportation directly afforded by the company.

The total value of the IL indicator is obtained summing the contributions of all the lifecycle phases according to the calculation formula provided here. Moreover, the calculation formulas of a subset of social indicators (namely Income Distribution, Worked Hours, Child Labor, and Local Supply) can be easily derived through substitution using the IL as reference (Table 3.45).

Table 3.45 IL calculation formula

3.5.1.8 Income Distribution Indicator Calculation Formula

The income distribution (ID) indicator measures the equity of the employee wage distribution within the solution space considering the weighted contribution of the company and its suppliers (the supply chain members) along the whole lifecycle of the product. For each supply chain member, the ID measures the ratio of the income of the top 10 % employees and the income of the bottom 10 % employees. The employees included in this evaluation are from labor to middle management.

For each lifecycle phase, the ID of each supply chain member contributing to this phase is assessed. Then the contribution of each supply chain member is weighted by means of the ratio of the unitary cost paid to the supplier and the sum of the unitary purchasing expenditures and the unitary variable cost of the solution space; the company contribution through the ratio of the unitary variable costs afforded by the company and the sum of the unitary purchasing expenditures and the unitary variable cost of the solution space. The weighted contributions are then summed along the product lifecycle phases in order to obtain the total value of the ID indicator.

The expected contributions to the ID indicators are the same as for the IL indicator as described in Sect. 3.5.1.7. The definition of the ID calculation formula is provided here, by offering a substitution table that allows to derive the ID calculus from the previous described IL formula, given its similarity due to the application of the same calculation method (Table 3.46).

Table 3.46 ID calculation formula through substitution

3.5.1.9 Worked Hours Indicator Calculation Formula

The worked hours (WH) indicator measures the number of worked hours per employee per week considering the weighted contribution of the company and its suppliers (the supply chain members) along the whole lifecycle of the product. The employees included in this evaluation are from labor to middle management.

For each lifecycle phase, the WH of each supply chain member contributing to this phase is assessed. Then the contribution of each supply chain member is weighted: the suppliers' contribution through the ratio of the unitary costs paid to the supplier and the sum of the unitary purchasing expenditures and the unitary variable cost incurred by the company; the company contribution through the ratio of the unitary variable costs afforded by the company and the sum of the unitary purchasing expenditures and the unitary variable cost of incurred by the company. The weighted contributions are then summed along the product lifecycle phases in order to obtain the total value of the WH indicator.

The expected contributions to the WH indicators are the same as for the IL indicator as described in Sect. 3.5.1.7. The definition of the WH calculation formula is provided here, by offering a substitution table that allows to derive the WH calculus from the previous described IL formula, given its similarity due to the application of the same calculation method (Table 3.47).

Table 3.47 WH calculation formula through substitution

3.5.1.10 Child Labor Indicator Calculation Formula

The child labor (CL) indicator measures the use of child labor within the solution space considering the weighted contribution of the company and its suppliers (the supply chain members) along the whole lifecycle of the product.

For each lifecycle phase, the use of child labor by each supply chain member contributing to this phase is assessed considering if the supply chain member uses or not children in its activity, neglecting the number of children used. Then the contribution of each supply chain member (indeed a 1 if it uses child labor, otherwise 0) is weighted: the suppliers' contribution through the ratio of the unitary costs paid to the supplier and the sum of the unitary purchasing expenditures and the unitary variable cost of the solution space; the company contribution through the ratio of the unitary variable costs afforded by the company and the sum of the unitary purchasing expenditures and the unitary variable cost of the solution space. The weighted contributions are then summed along the product lifecycle phases in order to obtain the total value of the CL indicator, obtaining a value included from 0 (no one is using children in its activity) to 1 (all supply chain members use children).

The expected contributions to the CL indicators are the same as for the IL indicator as described in Sect. 3.5.1.7. The definition of the CL calculation formula is provided here, by offering a substitution table that allows to derive the CL calculus from the previous described IL formula, given its similarity due to the application of the same calculation method (Table 3.48).

Table 3.48 CL calculation formula through substitution

3.5.2 Product Responsibility

3.5.2.1 Product Social Features Indicator Calculation Formula

The product social features (PSF) indicator measures the number of product features that aim at improving the condition of specific target groups (e.g., product for disabled, elderly, and diabetic people).

Since PSF merely measures the number of social features, a formula is not required. The design activities affecting the PSF indicator are those happening during the design phase through the formalization of customers requirements and relative selection of those features to be customized toward specific groups. To this end also social sustainability may result empowered by the application of mass customization options. No contributions are expected from the product lifecycle phases since the number of social features is determined at design level.

3.5.3 Local Community

3.5.3.1 Charitable Contribution Intensity Indicator Calculation Formula

The charitable contribution intensity (CCI) indicator is meant to measure the expenditure in charities within the solution space along the product lifecycles.

For each lifecycle phase, the first contribution described is about the company, while the next ones are about the suppliers. In each lifecycle phase, the charity expenditures made by the company department operating in that specific phase are allocated to the solution space and divided by the number of product expected to be produced in the product mix in order to obtain a unitary value. The allocation driver is the ratio of the turnover generated by the solution space and the total turnover of the company. The suppliers' contributions are indeed already unitary and allocated to the solution space. In each lifecycle phase, the charity expenditures made by each supplier are weighted through the ratio of the cost of the item or service provided and the sales turnover of the supplier. Then the contributions of each item are summed considering its frequency within the solution space. The suppliers’ contributions are structured so that the terms concerning the charity expenditures allocated to each item can be provided directly in the calculation formula of Table 3.49 or, in the future, retrieved from database whenever available.

Table 3.49 CCI calculation formula through substitution

The expected contributions to the CCI indicators are the same as for the II indicator as described in Sect. 3.5.1.1. The definition of the CCI calculation formula is provided here, by offering a substitution table that allows to derive the CCI calculus from the previous described RDII formula, given its similarity due to the application of the same intensity method.

3.5.3.2 Local Supply Indicator Calculation Formula

The local supply (LS) indicator measures the percentage of the purchasing expenditures related to items supplied from local suppliers considering the weighted contribution of the suppliers along the whole lifecycle of the product.

For each lifecycle phase each supplier is identified as local or not. Then the contribution of supplier (indeed a 1 if the supplier is local, 0 otherwise) is weighted through the ratio of the unitary costs paid to the supplier and the unitary purchasing expenditures. The weighted contributions are then summed along the product lifecycle phases in order to obtain the total value of the LS indicator, that is a value included from 0 (no suppliers are local) to 1 (all suppliers are local).

The expected contributions to the LS indicators are the same as for the IL indicator as described in Sect. 3.5.1.7. The definition of the LS calculation formula is provided here, by offering a substitution table that allows to derive the LS calculus from the previous described IL formula, given its similarity due to the application of the same calculation method (Table 3.50).

Table 3.50 LS calculation formula through substitution

3.6 Conclusions and Next Steps

This chapter addresses the development of the SAM assessment model. We start from its literature foundations through the definition of each single indicator along with its calculation formula.

With the development of this assessment model, a crucial cornerstone toward the concrete implementation of the Sustainable Mass Customization paradigm has been met. In fact, SAM deals with the issue of concretizing the effects of the decisions taken at design level down into numbers.

Selection of the indicators was focused on obtaining a homogeneous and balanced set of reliable indicators that measures the overall impact of all the entities involved in the product lifecycle on the three sustainability aspects. Such an ambitious target was never set in the existing literature so far and is meant to promote a real possibility to evaluate the performances of the Stable Solution Space for the companies as well as communicating in a transparent and reliable way the achieved improvements to customers.