Abstract

A hybrid batch fabrication plan involving an outsourcing option is often established to deal with the in-house capacity constraint and/or meet timely demand with a reduced cycle time. Besides, the occurrences of unpredictable equipment malfunction and imperfect product quality should also be effectively managed during in-house fabrication to meet the production schedule and the required quality level. To address these concerns, we examine a hybrid economic production quantity (EPQ) problem with an unreliable machine and quality reassurance; wherein, an outside provider helps supply a portion of the batch at a requested timing and desirable quality, but at the price of a higher than in-house unit cost. Corrective action is performed immediately when a Poisson-distributed breakdown occurs. Once the equipment repairing task completes, the interrupted lot’s fabrication resumes. Random nonconforming products are identified, and the re-workable items among them are separated from the scraps. A rework task follows the regular process in each cycle at an extra cost. A portion of reworked items fails and are scrapped. A model portraying the problem’s characteristics is built, and an optimization methodology is utilized to find the optimal runtime solution to the problem. A numerical example reveals our result’s applicability, and specific managerial implications are suggested.

Highlights

  • This study investigates a hybrid batch fabrication problem with Poisson-distributed equipment failures and rework/scrap of random nonconforming products. Taft (1918) determined the most economical manufacturing batch size under the assumption of a perfect fabrication process; neither machine failures nor defective items were considered, and all items are produced inhouse

  • We examine a hybrid economic production quantity (EPQ) problem with an unreliable machine and quality reassurance; wherein, an outside provider helps supply a portion of the batch at a requested timing and desirable quality, but at the price of a higher than in-house unit cost

  • For condition two that no random breakdown occurs during T1π, the total cost per cycle includes variable and fixed outsourcing costs, in-house variable and setup costs, safety stock’s holding cost, rework and disposal costs, holding cost for reworked items, perfect stocks, and defective items in T1π, t2π, and t3π

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Summary

Introduction

This study investigates a hybrid batch fabrication problem with Poisson-distributed equipment failures and rework/scrap of random nonconforming products. Taft (1918) determined the most economical manufacturing batch size under the assumption of a perfect fabrication process; neither machine failures nor defective items were considered, and all items are produced inhouse. This study investigates a hybrid batch fabrication problem with Poisson-distributed equipment failures and rework/scrap of random nonconforming products. Srinivasa Rao and Naikan (2014) proposed a hybrid method combining Markov modeling and system dynamics/simulation approach to analyze the repairable systems' reliability and behavior. The authors demonstrated their proposed framework for a standby system with repair using simulation. The authors compared previous ones with newly proposed rework strategies and highlighted their strengths and weaknesses in terms of various performance measurements, such as machine utilization, cycle time, the length of queues, fabrication cycle time, and quantity of work-in-process. For very few prior studies have explored the collective influence of Poisson-distributed equipment failures, quality reassurance, and outsourcing on the batch decision, we aim to fill the research gap

Description and modeling
Condition 2
Solution to the proposed problem
Algorithm for finding the T1π*
Numerical example
Influence of the main system factor on the problem
Joint influence of the core system factors on the problem
Conclusions
Full Text
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