Keywords

1 Introduction and Literature Review

In today scenario, lean manufacturing (LM) is not a new word in the manufacturing sector. Every grooving industry is focusing to implement of LM because of innovative strategies for better quality and best customer satisfaction [1]. It has been approved by entire worldwide for implementation in many industrial sectors, i.e. automobiles, fabrication, manufacturing and public sectors, for minimization of wastes. So it can be said that LM is not only used for manufacturing industries, but also used all over. LM is a mixture of different lean strategies which are 5’S, JIT TQM, TPM, lean training, kaizen, lean thinking, Kan-Ban, zero defect concept, VSM, Six Sigma, etc. [2]. LM delivers superior accuracy and improved productivity with high customer satisfaction with strategies like VSM [3].

After World War II, in Toyota motor company, Eiji Toyoda and Taiichi Ohno find out a way for better quality that was “Toyota Production System” and today is known as “lean system (LS)”. LS provide sets of maintenance for higher quality with fewer breakdowns [4]. According to [5], kaizen implementation with lean provides high quality in the industry. Here, industrial wastes can consider the activity such as value-added activity, nonvalue-added activity and necessary nonvalue-added activity. Wastes are unwanted in the industry as well as outside industry that can be eliminated, but it is also so difficult to eliminate. Kaizen is an effective strategy with continuous change for higher quality and better productivity. JIT is a pull system which prevents extra financially like excessive inventory and pressure on the industry. According to [6], lean is the successive agent to improve business scenario in current manufacturing era.

1.1 Research Need and Motivation

Here, question arises that which lean strategy is more effective in Indian manufacturing field. The Indian manufacturing sector is the fastest rising sector around the world. The manufacturing sector is the major pillar of the entire economic development of the country [7]. The manufacturing industries have been implemented LM and their strategies, but they do not know that which strategy is more effective. From last few years, Indian manufacturing industries are focusing on a best way to improve quality with minimum cost and best customer satisfaction, and this research will help them to identify [8]. If industries will know their prioritization with lean strategies, the industry quality will be high with good customer satisfaction. So it is very important to know lean strategies effectiveness as per their prioritization after the successful implementation of LM [9]. A successful implementation only can be possible if we have identified the system strong and weak points to improve [10].

1.2 Research Questions

  • To understand lean manufacturing concept

  • To study lean strategies

  • To explore the status of lean strategies by industrial experts

  • Prioritization of studied lean strategies

1.3 Research objective

  • Selection of LS

  • Selection of LS performance criteria

  • Select the prioritization method

  • Prioritization of LS based on selected LS performance criteria

There are so many techniques for prioritization for lean strategies, but grey relation analysis (GRA) is one of the most suitable methods for it [11]. After studying the literature, it is found that the GRA approach is a latent key for prioritization. GRA approach is used for multi-objective optimization which is practical on the calculated response results to select most preferred lean strategy in Indian manufacturing industry [12]. Response results are collected from different lean industrial experts from different industries with help of a well-designed questionnaire.

2 Methodology

This papers result to prioritization of lean strategies which are 5’S, JIT, TPM, TQM and lean training. These selected lean strategies are selected by literature review. These are more dominating as compared to other lean strategies. This prioritization is based on GRA theory, and required data have been collected from seven industrial experts which have good implementation knowledge about LM. These lean strategies will be rated with help of fuzzy Likert scale five with identified their LM selection criteria’s: cost, time, quality and flexibility. All required data will be collected with a well-oriented questionnaire. The linguistic response will be converted into fuzzy numbers and then rated with GRA.

2.1 Data Analysis

After prepare questionnaire, it is sent to different industrial experts to find the priority for the industry as per selected lean strategy selection criteria. Different seven expert’s data have been collected and got the average effect by the well-statistical tool to find the overall result. The responses have been arranged and shown in Table 1.

Table 1 Combined response of industrial experts
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Selection scale for cost and time is as follows: extremely high—5, very high—4, high—3, low—2, very low—1 (lower the better).

Selection scale for quality and flexibility is as follows: extremely high—1, very high—2, high—3, low—4, very low—5 (higher the better).

After arranging, the linguistic response result has been converted into the mathematical form shown in Table 2.

Table 2 Mathematical value response
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Every expert has a different opinion about the selection and prioritization of lean strategies. So it needs to make a common decision of all experts to prioritization lean strategies which is shown in Table 3. It can be solved with an average of all industrial expert response to make average response result.

Table 3 Average response result for all experts
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After making an average response, next step into implement GRA for best result individual for all lean strategies select criteria’s which are cost, time, quality and flexibility (Tables 4, 5, 6 and 7).

Table 4 GRA analysis for cost
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Table 5 GRA analysis for time
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Table 6 GRA analysis for quality
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Table 7 GRA analysis for flexibility
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Similarly, weight shown in Table 8 is the average given by the different industrial experts, and it can vary as per the industry implementation, where industrial weight can be varied according to industries which implement LS.

Table 8 Weight for lean strategy selection criteria by experts
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2.2 Method to Apply GRA

Normalize the collected data shown in Tables 4, 5, 6 and 7.

After normalizing, all data will be between 0 and 1.

$$ x^{*}_{1} (t) = \frac{{\max_{i} (t) - x_{1i} (t)}}{{\max_{i} (t) - \min_{i} (t)}} $$
(1)

Identify deviation value with normalized data shown in Tables 4, 5, 6 and 7.

$$ Dx_{1} (t) = 1 - x^{*}_{1} (t) $$
(2)

Computation of grey relational coefficients (GRCs) is noted with ξ (t), and normally value is taken as 0.5.

Computation of grey relational grade (GRG) is shown in Table 9.

Table 9 Calculation of grey relational grade (GRG)
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GRC will be the multiple of all GRC values with their related weight given by experts and then the summation of all, i.e.

$$ \begin{aligned} {\text{GRG}}\,{\text{for}}\, 5 \textquoteright {\text{S}} = & {\text{GRC}}\left( {\text{cost}} \right)*{\text{Wc}} + {\text{GRC}}\left( {\text{time}} \right)*{\text{Wt}} + {\text{GRC}}\left( {\text{quality}} \right)*{\text{Wq}} \\ & + {\text{GRC}} \left( {\text{flexibility}} \right)*{\text{Wf}} = 0.395 \\ \end{aligned} $$
(3)

Similarly, GRG results for other lean strategies are shown in Table 9 (Fig. 1).

Fig. 1
figure 1

Chart 1—GRG value for lean strategies

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3 Results and Conclusion

After the complete study, it is found that GRA theory is very precise and effective to reflect the well-maintained prioritization of implemented lean strategies. As per the industrial present competitive behaviour, lean strategies must be prioritization and GRA theory has very effective results. As result shown in Chart 1, it is clear that TQM is more dominating for manufacturing industry. JIT is in second position, and lean training is at number third. The whole study is based on survey analysis of different industries that know and implemented lean manufacturing. 5’S, JIT, TPM, TQM and lean training are the most useful and implemented strategies for manufacturing industries, so these are considered. After GRC identification, a sole result comes out about lean strategies, but the next thing which will affect is related weight. This weight will be given by industry. For further study, individual industry can be analysed to find its relative priority. Also, we can consider different lean strategies and different other industries for better results.

Future researcher can consider remaining lean strategies and can consider more industries to make research more precise and accurate in present Indian scenario.