Dynamic lot-sizing with rework of defective items and minimum lot-size constraints

2015 ◽  
Vol 54 (8) ◽  
pp. 2284-2297 ◽  
Author(s):  
Andreas Goerler ◽  
Stefan Voß
2016 ◽  
Vol 33 (03) ◽  
pp. 1650018
Author(s):  
Chung-Lun Li ◽  
Qingying Li

There has been a lot of research on dynamic lot sizing problems with different nonlinear cost structures due to capacitated production, minimum order quantity requirements, availability of quantity discounts, etc. Developing optimal solutions efficiently for dynamic lot sizing models with nonlinear cost functions is a challenging topic. In this paper, we present a set of sufficient conditions such that if a single-item dynamic lot sizing problem satisfies these conditions, then the existence of a polynomial-time solution method for the problem is guaranteed. Several examples are presented to demonstrate the use of these sufficient conditions.


2020 ◽  
Vol 37 (6/7) ◽  
pp. 873-904
Author(s):  
Mohamed Ali Kammoun ◽  
Zied Hajej ◽  
Nidhal Rezg

PurposeThe main contribution of this manuscript is to suggest new approaches in order to deal with dynamic lot-sizing and maintenance problem under aspect energetic and risk analysis. The authors introduce a new maintenance strategy based on the centroid approach to determine a common preventive maintenance plan for all machines to minimize the total maintenance cost. Thereafter, the authors suggest a risk analysis study further to unforeseen disruption of availability machines with the aim of helping the production stakeholders to achieve the obtained forecasting lot-size plan.Design/methodology/approachThe authors tackle the dynamic lot-sizing problem using an efficient hybrid approach based on random exploration and branch and bound method to generate possible solutions. Indeed, the feasible solutions of random exploration method are used as input for branch and bound to determine the near-optimal solution of lot-size plan. In addition, our contribution to the maintenance part is to determine the optimal common maintenance plan for M machines based on a new algorithm called preventive maintenance (PM) periods means.FindingsFirst, the authors have funded the optimal lot-size plan that should satisfy the random demand under service level requirement and energy constraint while minimizing the costs of production and inventory. Indeed, establishing a best lot-size plan is to determine the appropriate number of available machines and manufactured units per period. Second, for risk analysis study, the solution of subcontracting is proposed by specifying a maximum cost of subcontractor in the context of a calling of tenders.Originality/valueFor maintenance problem, the originality consists in regrouping the maintenance plans of M machines into only one plan. This approach lets us to minimize the total maintenance cost and reduces the frequent breaks of production. As a second part, this paper contributed to the development of a new risk analysis study further to unforeseen disruption of availability machines. This risk analysis developed a decision-making system, for production stakeholders, in order to achieve the forecasting lot-size plan and keeps its profitability, by specifying the unit cost threshold of subcontractor in the context of a calling of tender.


1970 ◽  
Vol 38 ◽  
pp. 1-7 ◽  
Author(s):  
Sultana Parveen ◽  
AFM Anwarul Haque

The multi-item single level capacitated dynamic lot-sizing problem consists of scheduling N items over a horizon of T periods. The objective is to minimize the sum of setup and inventory holding costs over the horizon subject to a constraint on total capacity in each period. No backlogging is allowed. Only one machine is available with a fixed capacity in each period. In case of a single item production, an optimal solution algorithm exists. But for multi-item problems, optimal solution algorithms are not available. It has been proved that even the two-item problem with constant capacity is NP (nondeterministic polynomial)-hard. That is, it is in a class of problems that are extremely difficult to solve in a reasonable amount of time. This has called for searching good heuristic solutions. For a multi-item problem, it would be more realistic to consider an upper limit on the lot-size per setup for each item and this could be a very important parameter from practical point of view. The current research work has been directed toward the development of a model for multi-item problem considering this parameter. Based on the model a program has been executed and feasible solutions have been obtained. Keywords: Heuristics, inventory, lot-sizing, multi-item, scheduling.DOI: 10.3329/jme.v38i0.893 Journal of Mechanical Engineering Vol.38 Dec. 2007 pp.1-7


2016 ◽  
Vol 4 (1) ◽  
pp. 75
Author(s):  
Fu C. Chyr ◽  
Shan Y. Huang

<p><em>The primary topic of operation management has turned to setup cost reduction because of the success of Just-in-</em><em>T</em><em>ime (JIT) system. Setup cost is treated as a policy variable that can be reduced. A few papers prove that setup cost reduction will increase the number of setups and approach to JIT. However, those papers do not discuss the maximum setup time allowed that will successfully achieve to JIT. The Wagner-Whitin (WW) algorithm is known to produce optimal lot size for T-period dynamic lot-sizing problems. This paper develops an extension of the WW algorithm to establish a recursive model and find the sufficient</em><em> </em><em>and necessary conditions of yielding JIT. Furthermore, the limited</em><em> </em><em>maximum setup time that will yield JIT system is discussed. The maximum setup time of achieving JIT can be easily computed and understood in practice. The formula and table of the setup time allowed are obtained to act as a goal of reducing setup time in JIT system.</em></p>


2019 ◽  
Vol 4 (2) ◽  
pp. 205-214
Author(s):  
Erika Fatma

Lot sizing problem in production planning aims to optimize production costs (processing, setup and holding cost) by fulfilling demand and resources capacity costraint. The Capacitated Lot sizing Problem (CLSP) model aims to balance the setup costs and inventory costs to obtain optimal total costs. The object of this study was a plastic component manufacturing company. This study use CLSP model, considering process costs, holding costs and setup costs, by calculating product cycle and setup time. The constraint of this model is the production time capacity and the storage capacity of the finished product. CLSP can reduce the total production cost by 4.05% and can reduce setup time by 46.75%.  Keyword: Lot size, CLSP, Total production cost.


2006 ◽  
Vol 38 (11) ◽  
pp. 1027-1044 ◽  
Author(s):  
Ayhan Özgür Toy ◽  
Emre Berk

1995 ◽  
Vol 26 (9) ◽  
pp. 1593-1600
Author(s):  
CHING-JONG LIAO ◽  
TSUNG-SHIN HSU

2014 ◽  
Vol 933 ◽  
pp. 860-868
Author(s):  
Muneam Zamzeer Al-Magsoosi

Successful implementation of ERP systems should take full advantage of the access to information, but not be constrained by many of the deficiencies associated with infinite capacity scheduling methodologies. In this paper an algorithm is developed which improves the performance of the ERP system. Lot sizing decisions based on capacity availability are used as an instrument to integrate more effectively capacity requirements planning (CRP) and Material Requirements Planning (MRP). MRP is a planning tool for a sub-set of manufacturing system specially in hierarchal multi-product, multi-period and multi-stage production planning and inventory control system. The Vehicle used for this integration is planned order release (POR) quantity. The algorithm requires minimal deviation from the MRP logic. In this sequential process MRP first issues the action notices and then the algorithm analyses the capacity situation in the work centers. The algorithm scans all planned order release quantities of lower level items in the action bucket before orders are released to the shop. For each item a delta value is computed identifying the degree orders are contributing to capacity problems. This delta is specific to each POR. The POR causing the highest overload and the one passing through the lowest utilized work centers are selected for a lot size decrease, respectively, an increase. After identifying the candidates, a series of checks analyses the suitability of the candidates for that change. The planned order release quantities of more items can be performed. Projected capacity profile after iteration will be updated and capacity requirements over a short duration are smoothed. The experiments are performed with MAP/3000 as a simulation model for this study. The developed algorithm is added to MAP/3000 as additional subroutines. The design of the experiments consists of a base test identifying the significance of different environmental parameters of MRP systems and a main test which performs a detailed evaluation. The results are evaluated using analysis of variance techniques. Most ERP systems built on the historical development of MRP and CRP systems, and the assumption of infinite capacity is affecting the performance of those systems badly. This paper is presenting an algorithm to smooth capacity problems by using the existed capacity.


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