Transformation of a production/assembly washing machine lines into a lean manufacturing system

The scope of this work is the complete re-organization of production flow according to the Lean Thinking philosophy for the industrial applications. The complete re-organization implementation of material flow management has been performed through the supermarket sizing which replenishment kanban logic has been adopted. To implement this strategy the goal is to achieve "Interdependent connected Processes" adopting the Pull System methodology in the Just in Time production environment. From the narrow sense the JIT manufacturing philosophy is to produce the right quantity at the right time with the right quantity level. In JIT the production is triggered by a kanban signal, which comes from the costumer order or the master production schedule, the signal then flowing backwards. By implementing JIT concepts in manufacturing, many of the practitioners experience advantages such as shorter lead times, fewer inventories, and higher quality. In the case study, developed in the Whirlpool Europe Naples factory, we have a first stage that consists of sizing the amount of "Kanban reintegration" codes, and the second stage in which we have simulated with ARENA and verified the progress of production flow in the hypothesized system, that has underlined the improvement of the business performances and great flexibility.

[1]  Andrew Kusiak,et al.  Overview of Kanban systems , 1996 .

[2]  J. Liker The Toyota Way , 2003 .

[3]  Izak Duenyas,et al.  Optimal Policies for Inventory Systems with Priority Demand Classes , 2003, Oper. Res..

[4]  Thomas J. Schriber,et al.  An introduction to simulation using GPSS/H , 1991 .

[5]  Robert G. Sargent Event Graph Modelling for Simulation with an Application to Flexible Manufacturing Systems , 1988 .

[6]  Jeffrey K. Liker,et al.  The Toyota way : 14 management principles from the world's greatest manufacturer , 2004 .

[7]  Behnam Pourbabai Loading strategies for a class of just-in-time manufacturing system , 1995 .

[8]  W. David Kelton Statistical analysis of simulation output , 1997, WSC '97.

[9]  A. Alan B. Pritsker,et al.  Introduction to simulation and SLAM II , 1979 .

[10]  Yunzeng Wang,et al.  Differentiating customer service on the basis of delivery lead-times , 2002 .

[11]  Felix T.S. Chan Effect of kanban size on just-in-time manufacturing systems , 2001 .

[12]  Randall P. Sadowski,et al.  Simulation with Arena , 1998 .

[13]  Jerry Banks Introduction to simulation , 1999, WSC '99.

[14]  Özalp Özer,et al.  Integrating Replenishment Decisions with Advance Demand Information , 2001, Manag. Sci..

[15]  M. C. Bonney,et al.  Simulation and Analysis of Industrial Systems , 1971 .

[16]  Luciane Neves Canha,et al.  Experimental design and models of power system optimization and control , 2007 .

[17]  Paul H. Zipkin,et al.  Customer-order information, leadtimes, and inventories , 1995 .

[18]  Mehmet Savsar Simulation analysis of a pull-push system for an electronic assembly line , 1997 .

[19]  Lee Luong,et al.  Optimization/simulation modelling of the integrated production-distribution plan: an innovative survey , 2008 .

[20]  Claude Dennis Pegden Introduction to SIMAN , 1988, WSC '88.

[21]  J. Wijngaard,et al.  The effect of foreknowledge of demand in case of a restricted capacity: The single-stage, single-product case , 2004, Eur. J. Oper. Res..

[22]  G SargentRobert Statistical analysis of simulation output data , 1977 .

[23]  Yves Dallery,et al.  Integrating advance order information in make-to-stock production systems , 2002 .

[24]  John Craig Comfort The simulation of a master-slave event set processor , 1984 .

[25]  Averill M. Law Statistical Analysis of Simulation Output Data , 1980 .

[26]  Randall P. Sadowski,et al.  Introduction to Simulation Using Siman , 1990 .

[27]  Fangruo Chen,et al.  Market Segmentation, Advanced Demand Information, and Supply Chain Performance , 2000, Manuf. Serv. Oper. Manag..

[28]  Armin Scholl,et al.  A survey on problems and methods in generalized assembly line balancing , 2006, Eur. J. Oper. Res..

[29]  Averill M. Law,et al.  Simulation Modeling & Analysis , 1991 .

[30]  Nils Boysen,et al.  A classification of assembly line balancing problems , 2007, Eur. J. Oper. Res..

[31]  George Liberopoulos,et al.  Tradeoffs between base stock levels, numbers of kanbans, and planned supply lead times in production/inventory systems with advance demand information , 2005 .

[32]  Jeffrey K. Liker,et al.  The Toyota way fieldbook : a practical guide for implementing Toyota's 4Ps , 2004 .

[33]  Paul R. Kleindorfer,et al.  Service Constrained s, S Inventory Systems with Priority Demand Classes and Lost Sales , 1988 .

[34]  Rakesh Nagi,et al.  Integrated lot-sizing and scheduling for just-in-time production of complex assemblies with finite set-ups , 1997 .

[35]  Ananth Krishnamurthy,et al.  Pull systems with advance demand information , 2005, Proceedings of the Winter Simulation Conference, 2005..

[36]  Pyoung Yol Jang Evolution structure of a process and resource models-based simulation for the supply chain management , 2007 .

[37]  Yves Dallery,et al.  The Value of Advance Demand Information in Production/Inventory Systems , 2004, Ann. Oper. Res..

[38]  G. Stalk,et al.  Competing on capabilities: the new rules of corporate strategy. , 1992, Harvard business review.

[39]  Roberto Revetria,et al.  An agent-based system for sales and operations planning in manufacturing supply chains , 2007 .