From loop structure to policy-making: a CONWIP design framework for hybrid flow shop control in one-of-a-kind production environment

A feasible constant work in process (CONWIP) policy can guide developer to better implement CONWIP system. The feasible policy should be selected from alternatives by evaluation. Therefore, how to generate more than one CONWIP alternative policy to evaluate is an inevitable problem in CONWIP practice. From the perspective of loop structure, we propose CONWIP design framework (CDF) which is a systematic design approach to obtain CONWIP alternative policies. The basic concepts and components for CDF are discussed in this paper. Based on CDF, we make 10 CONWIP alternative policies for hybrid flow shop in one-of-a-kind production environment, and these alternative policies are evaluated by simulation. The simulation result implies that (i) the CONWIP alternative policy with robustness has the potential to cope with more fluctuations in high-variety production environment; (ii) a better design for CONWIP policy will be able to enhance the system performance in practice; and (iii) the loop structure can serve as a parameter of CONWIP.

[1]  Charles H. Smith,et al.  Selecting allowance policies for improved job shop performance , 1993 .

[2]  T.C.E. Cheng,et al.  Job shop scheduling for missed due-date performance , 1998 .

[3]  Alain Guinet,et al.  Reduction of job-shop problems to flow-shop problems with precedence constraints , 1998, Eur. J. Oper. Res..

[4]  S.M.T. Fatemi Ghomi,et al.  Hybrid flow shop scheduling with sequence dependent family setup time and uncertain due dates , 2014 .

[5]  Jie Chen,et al.  An approach of designing CONWIP loop for assembly system in one-of-a-kind production environment , 2016, Int. J. Comput. Integr. Manuf..

[6]  Wenxin Liu,et al.  A neural network model and algorithm for the hybrid flow shop scheduling problem in a dynamic environment , 2005, J. Intell. Manuf..

[7]  Shouyang Wang,et al.  Information and decision-making delays in MRP, KANBAN, and CONWIP , 2014 .

[8]  Mostafa Zandieh,et al.  An efficient bi-objective heuristic for scheduling of hybrid flow shops , 2011 .

[9]  Steven Harrod,et al.  Applying work flow control in make-to-order job shops , 2013 .

[10]  Jing-Wen Li Simulation study of coordinating layout change and quality improvement for adapting job shop manufacturing to CONWIP control , 2010 .

[11]  Jatinder N. D. Gupta,et al.  Heuristics for hybrid flow shops with controllable processing times and assignable due dates , 2002, Comput. Oper. Res..

[12]  Alain Bernard One-of-a-kind production , 2014 .

[13]  Suna Kondakci Köksalan,et al.  A flexible flowshop problem with total flow time minimization , 2001, Eur. J. Oper. Res..

[14]  Charles A. Holloway,et al.  Job Shop Scheduling with Due Dates and Variable Processing Times , 1974 .

[15]  R. M. Hodgson,et al.  JOB SHOPS SCHEDULING WITH DUE DATES , 1967 .

[16]  Shigeru Fujimura,et al.  Dynamic routing strategies for JIT production in hybrid flow shops , 2012, Comput. Oper. Res..

[17]  N. Zeev,et al.  Controlling shop floor operations in a multi-family, multi-cell manufacturing environment through constant work-in-process , 1999 .

[18]  Yaghoub Khojasteh-Ghamari A performance comparison between Kanban and CONWIP controlled assembly systems , 2009, J. Intell. Manuf..

[19]  Nihat Yüzügüllü,et al.  Dynamic job shop scheduling for missed due date performance , 2009 .

[20]  Rainer Leisten,et al.  Input control and dispatching rules in a dynamic CONWIP flow-shop , 2000 .

[21]  Deyi Xue,et al.  An information system for one-of-a-kind production , 2009 .

[22]  SARAH M. RYAN,et al.  Determining inventory levels in a CONWIP controlled job shop , 2000 .

[23]  Geun-Cheol Lee,et al.  Estimating order lead times in hybrid flowshops with different scheduling rules , 2009, Comput. Ind. Eng..

[24]  Jose M. Framinan,et al.  The CONWIP production control system: Review and research issues , 2003 .

[25]  Dong-Ho Lee,et al.  Scheduling algorithms to minimize the number of tardy jobs in two-stage hybrid flow shops , 2009, Comput. Ind. Eng..

[26]  V. Vinod,et al.  Simulation modeling and analysis of due-date assignment methods and scheduling decision rules in a dynamic job shop production system , 2011 .

[27]  S. Ryan,et al.  Total WIP and WIP mix for a CONWIP controlled job shop , 2003 .

[28]  David L. Woodruff,et al.  CONWIP: a pull alternative to kanban , 1990 .

[29]  Jose M. Framinan,et al.  On transforming job-shops into flow-shops , 2002 .

[30]  James K. Weeks A Simulation Study of Predictable Due-Dates , 1979 .

[31]  Feng Chu,et al.  Minimising the weighted number of tardy jobs in a hybrid flow shop with genetic algorithm , 2009, Int. J. Comput. Integr. Manuf..

[32]  Anders Segerstedt,et al.  Restricted work-in-process: A study of differences between Kanban and CONWIP , 2009 .

[33]  Deyi Xue,et al.  Optimal resource allocation for hybrid flow shop in one-of-a-kind production , 2010, Int. J. Comput. Integr. Manuf..

[34]  Jannes Slomp,et al.  A lean production control system for high-variety/low-volume environments: a case study implementation , 2009 .

[35]  Christos Koulamas,et al.  A note on weighted completion time minimization in a flexible flow shop , 2001, Oper. Res. Lett..

[36]  Xiuli Wang,et al.  A simulation study of CONWIP assembly with multi-loop in mass production, multi-products and low volume and OKP environments , 2015 .

[37]  Bernd Scholz-Reiter,et al.  Toward learning autonomous pallets by using fuzzy rules, applied in a Conwip system , 2012, The International Journal of Advanced Manufacturing Technology.

[38]  Boaz Golany,et al.  Controlling shop floor operations in a multi-family, multi-cell manufacturing environment through constant work-in-process , 1999 .

[39]  Samuel Eilon,et al.  Due dates in job shop scheduling , 1976 .

[40]  Joshua Prakash,et al.  Modified CONWIP systems: a review and classification , 2014 .