Abstract
As mass customization companies grow their business, the amount of custom information required to run the business increases. This paper proposes an information technology (IT) framework to solve this problem through automatic generation of information. The framework uses the concept of information templates or models and a rule-based system to generate manufacturing instructions. The templates combine the knowledge of bill-of-materials and resources while applying constraints to ensure the resulting custom product conforms to performance specifications. The feasibility and effectiveness of the framework and concepts are empirically validated by a case study implementation at a company that mass produces customized windows and doors in Calgary, Canada.
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References
Davis S (1997) Future perfect. Perseus Books Group, New York
Pine BJ (1999). Mass customization: the new frontier in business competition. Harvard Business School Press, UK
Piller FT (2002) Customer interaction and digitization - a structured approach to mass customization. Moving into mass customization: Information systems and management principle, part II, pp 119–137, Springer, Berlin
Krajewski LJ, Ritzman LP (2002) Forecasting. Operations Management, Editors: Tucker T, Boardman PJ, Surich S, 6th edition, pp 539, Prentice Hall, New Jersey
Krajewski LJ, Ritzman LP (2002) Resource Planning. Operations Management, Editors: Tucker T, Boardman PJ, Surich S, 6th edn, pp 731–780, Prentice-Hall, Upper Saddle River, NJ
Jin G, Thomson V (2003) A new framework for MRP systems to be effective in engineered-to-order environments. Robot Comput Integr Manuf 19:533–541
Yan HS, Zhang XD, Ma XD (2002) Karmarkar’s and interaction/prediction algorithms for hierarchical production planning for the highest business benefit. Comput Indust 49:141–155
Feiring B (1991) Production planning in stochastic demand environments. Mathl Comput Model 15(10):91–95
Vandaele N, de Boeck L (2003) Advanced resource planning. Robot Comput Integr Manuf 19:211–218
Kubat C, Taskin H, Topal B (2003) Comparison of OR and AI methods in discrete manufacturing using fuzzy logic. J Int Manuf 15:517–526
Ming XG, Mak KL, Yan JQ (1999) A hybrid intelligent inference model for computer aided process planning. Integr Manuf Systems 10(6):343–353
Kuo RJ, Wu P, Wnag CP (2002) An intelligent sales forecasting system through integration of artifical neural networks and fuzzy neural networks with fuzzy weight elimination. Neural Netw 15:909–925
Priore P, Fuente D, Pino R, Puente J (2003) Dynamic scheduling of flexible manufacturing systems using neural networks and inductive learning. Integr Manuf Syst 14(2):160–168
Jiao JX, Zhang YY (2005) Modeling of modularity and scaling for integration of customer in design of engineer-to-order products. Comput Aid Des 37(2):149–172
Shao XY, Wang ZH, Li PG, Feng CXJ (2006) Integrating data mining and rough set for customer group-based discovery of product configuration rules. Int J Prod Res 44(14):2789–2811
Svensson C, Barford A (2002) Limits and opportunities in mass customization for ‘build-to-order’ SME’s. Computers in Industry 49:77–89
Kotha S (1996) From mass production to mass customization: the case of the national industrial bicycle company of Japan. Eur Manage J 14:442–450
MacCarthy B, Brabazon PG, Bramham J (2003) Fundamental modes of operation for mass customization. Int J Prod Econ 85:289–304
Selladurai RS (2003) Mass customization in operations management: Oxymoron or Reality OMEGA. Int J of Manag Sc 32
Frutos JD, Borenstein D (2004) A framework to support customer-company interaction in mass customization environments. Comput Ind 54:115–135
Yao AN, Yang X, Rong Y (2007) Computer aided manufacturing planning for mass customization: part3, information modeling. Int J Adv Manuf Technol 32(1–2):218–228
Siddique Z, Ninan JA (2006) Product portfolio identification based on association rule mining. Integr Comput Aid Eng 13(2):133–148
Mukhopadhyay SK, Setoputro R (2005) Optimal return policy and modular design for build-to-order products. J Oper Manage 23(5):496–506
Guangming Z, Yujin H, Xuelin W, Chenggang L (2004) The representation of conceptual product based on component-connector design feature with P/T net approach. Int J Adv Manuf Technol 26:1193–1201
Rolstadas A (1991) ESPRIT basic research action No. 3143 - FOF production theory. Comput Ind 16:129–139
Hegge HMH, Wortmann JC (1991) Generic bill-of-material: A new product model. Int J of Prod Econ 23:17–128
Du X, Jiao J, Tseng M (2002) Graph grammar based product family modeling. Concurrent Eng: Res Appl 10(2):113–128
Huang GQ, Zhang XY, Liang L (2005) Towards integrated optimal configuration of platform products, manufacturing processes, and supply chains. J of Ops Manag 23:267–290
Tu YL, Chu XL, Yang WY (2000) Computer aided process planning in virtual one-of-a-kind production. Comput Ind 41:99–110
Tu YL, Xie SQ (2001) An information modeling framework to support sheet metal parts intelligent concurrent design and manufacturing. Int J of Adv Manuf Technol 18:873–883
Tu YL (2002) Automatic scheduling and control of a ship web welding assembly line. Comput Ind 29(3):159–171
Jinsong Z, Qifu W, Li W, Yifang Z (2004) Configuration-oriented product modeling management for made-to-order manufacturing enterprises. Int J Adv Manuf Technol 25:41–52
Li B, Chen L, Huang Z, Zhong Y (2005) Product configuration optimization using a multi-objective genetic algorithm. Int J Adv Manuf Technol 30:20–29
Zeng FS, Jin Y (2006) Study on product configuration based on product model. Int J Adv Manuf Technology 33:766–771
Matta A, Semeraro Q (2005) A framework for long term capacity decisions in AMSS. Design of advanced manufacturing systems. Springer, Berlin
Luger GF (2002) Expert system technology. Artificial Intelligence, 4th edn. Addison-Wesley, Harlow, England, pp 249–250
Fujimoto H, Ahmed A (2003) Assembly process design for managing manufacturing complexities because of product varieties. Int J Flex Manuf Syst 15:283–307
Padhy NP (2005) Expert systems. Artificial intelligence and intelligent systems. Oxford University Press, India, Ch 6:278–335
Padhy NP (2005) Fuzzy systems. Artificial intelligence and intelligent systems. Oxford University Press, India, Ch 7:336–399
Weiss MA (1999) Linked list. In: Hartman S, Harutunian K, Unubun P (eds), Data structures & algorithm analysis in Java. Addison Wesley Longman, Reading, MA, pp 56–57
Booch G (1990) In: Apt A, Telatnik MA (eds) Object oriented design with applications. Benjamin/Cummingsy, San Francisco, CA
Scott ML (2000) Recursion and Macros. In: Penrose EM, Wade M (eds), Programming language pragmatics, 6.6. Academic, San Diego, CA, pp 297–303
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Dean, P.R., Tu, Y.L. & Xue, D. A framework for generating product production information for mass customization. Int J Adv Manuf Technol 38, 1244–1259 (2008). https://doi.org/10.1007/s00170-007-1171-0
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DOI: https://doi.org/10.1007/s00170-007-1171-0