Mathematical modeling of a multi-product EMQ model with an enhanced end items issuing policy and failures in rework

Abstract This study uses mathematical modeling to examine a multi-product economic manufacturing quantity (EMQ) model with an enhanced end items issuing policy and rework failures. We assume that a multi-product EMQ model randomly generates nonconforming items. All of the defective are reworked, but a certain portion fails and becomes scraps. When rework process ends and the entire lot of each product is quality assured, a cost reduction n + 1 end items issuing policy is used to transport finished items of each product. As a result, a closed-form optimal production cycle time is obtained. A numerical example demonstrates the practical usage of our result and confirms a significant savings in stock holding and overall production costs as compared to that of a prior work (Chiu et al. in J Sci Ind Res India, 72:435–440 2013) in the literature.

[1]  Navonil Mustafee,et al.  A game-based approach towards facilitating decision making for perishable products: An example of blood supply chain , 2014, Expert Syst. Appl..

[2]  David F. Pyke,et al.  Inventory management and production planning and scheduling , 1998 .

[3]  Ming-Hon Hwang,et al.  Replenishment lot sizing with failure in rework and an enhanced multi-shipment policy , 2014 .

[4]  Michael Godfrey,et al.  Incorporating transportation costs into inventory replenishment decisions , 2002 .

[5]  Ron S. Kenett,et al.  The impact of defects on a process with rework , 1995 .

[6]  Christoph H. Glock,et al.  The Lot Sizing Problem: A Tertiary Study , 2014 .

[7]  Felix Hueber,et al.  Production And Operations Analysis , 2016 .

[8]  Mehdi Safaei,et al.  An integrated multi-objective model for allocating the limited sources in a multiple multi-stage lean supply chain , 2014 .

[9]  Yigal Gerchak,et al.  Multistage Production to Order with Rework Capability , 2002, Manag. Sci..

[10]  Mei-fang Wu,et al.  Optimization of a multi-product EPQ model with scrap and an improved multi-delivery policy , 2014 .

[11]  James A. Rodger,et al.  Application of a Fuzzy Feasibility Bayesian Probabilistic Estimation of supply chain backorder aging, unfilled backorders, and customer wait time using stochastic simulation with Markov blankets , 2014, Expert Syst. Appl..

[12]  R. W. Grubbström,et al.  A century of evolution from Harris׳s basic lot size model: Survey and research agenda , 2014 .

[13]  A. Banerjee A JOINT ECONOMIC-LOT-SIZE MODEL FOR PURCHASER AND VENDOR , 1986 .

[14]  Qiong Mou,et al.  A note on “lead time reduction strategies in a single-vendor-single-buyer integrated inventory model with lot size-dependent lead times and stochastic demand” , 2017 .

[15]  D. Battini,et al.  A sustainable EOQ model: Theoretical formulation and applications , 2014 .

[16]  D. Battini,et al.  Consignment stock inventory policy: methodological framework and model , 2010 .

[17]  Arthur F. Veinott,et al.  Analysis of Inventory Systems , 1963 .

[18]  C. Glock The joint economic lot size problem: A review , 2012 .

[19]  Peter L. Jackson,et al.  Efficient computation of time-based customer service levels in a multi-item, multi-echelon supply chain: A practical approach for inventory optimization , 2009, Eur. J. Oper. Res..

[20]  Christoph H. Glock,et al.  Lead time reduction strategies in a single-vendor–single-buyer integrated inventory model with lot size-dependent lead times and stochastic demand , 2012 .

[21]  Manickam Murugan,et al.  Productivity improvement in manufacturing submersible pump diffuser housing using lean manufacturing system , 2014 .

[22]  Ming-Hon Hwang,et al.  Optimal common cycle time for a multi-item production system with discontinuous delivery policy and failure in rework , 2013 .

[23]  Ruhul A. Sarker,et al.  A recovery mechanism for a two echelon supply chain system under supply disruption , 2014 .

[24]  Christoph H. Glock,et al.  A multiple-vendor single-buyer integrated inventory model with a variable number of vendors , 2011, Comput. Ind. Eng..

[25]  Herbert Jodlbauer,et al.  Optimizing service-level and relevant cost for a stochastic multi-item cyclic production system , 2012 .

[26]  Boray Huang,et al.  On a multi-product lot scheduling problem subject to an imperfect process with standby modules , 2014 .

[27]  Maurizio Faccio,et al.  Inventory holding costs measurement : a multi-case study , 2014 .

[28]  Yuan-Shyi Peter Chiu,et al.  Optimal run time for EPQ model with scrap, rework and stochastic breakdowns: A note , 2014 .

[29]  Hui-Ming Wee,et al.  An economic production quantity model with non-synchronized screening and rework , 2014, Appl. Math. Comput..

[30]  Angappa Gunasekaran,et al.  Consignment stock inventory model in an integrated supply chain , 2010 .

[31]  Awi Federgruen,et al.  Determining Production Schedules Under Base-Stock Policies in Single Facility Multi-Item Production Systems , 1998, Oper. Res..

[32]  Joaquín Sicilia,et al.  Policies for a single-vendor multi-buyer system with finite production rate , 2008, Decis. Support Syst..

[33]  Kenji Muramatsu,et al.  A Near-Optimal Solution Method of Multi-Item Multi-Process Dynamic Lot Size Scheduling Problem , 2003 .

[34]  Katherinne Salas Navarro,et al.  A three layer supply chain model with multiple suppliers, manufacturers and retailers for multiple items , 2014, Appl. Math. Comput..

[35]  Bhaba R. Sarker,et al.  Optimal batch quantity models for a lean production system with in-cycle rework and scrap , 2008 .

[36]  Christoph H. Glock,et al.  Batch sizing with controllable production rates in a multi-stage production system , 2011 .

[37]  Meir J. Rosenblatt,et al.  An application of a grouping procedure to a multi-item production system , 1983 .