An Integrated Methodology for Order Release and Scheduling in Hybrid Manufacturing Systems

Handbook of Research on Applied Optimization Methodologies in Manufacturing Systems - Advances in Logistics, Operations, and Management Science ◽

10.4018/978-1-5225-2944-6.ch007 ◽

2018 ◽

pp. 125-161

Author(s):

Ömer Faruk Yılmaz ◽

Mehmet Bülent Durmuşoğlu

Keyword(s):

Manufacturing Systems ◽

Holistic Approach ◽

Flow Time ◽

Batch Scheduling ◽

Hybrid Manufacturing ◽

Effective Solution ◽

Expansion Joints ◽

Order Release ◽

Feasible Solutions ◽

Alternative Solutions

There are three main problems that could impact the performance of a Hybrid Manufacturing System (HMS): (1) order release (OR), (2) batch scheduling and (3) worker assignment. This paper deals with these three main problems hierarchically for an HMS. Three different mathematical models are developed to describe the problems more clearly. A novel methodology is proposed to adopt a holistic approach to these problems and find an effective solution. Implementation of the proposed methodology permits integrating batch scheduling and worker timetabling. Feasible solutions in the best-known Pareto front are evaluated as alternative solutions. The goal is to select a preferred solution that satisfies worker constraints, creates effective worker teams in cells, minimizes the number of utility workers, and the average flow time. The study also presents several improvements, which are made following the application of the proposed methodology to a real company that produces expansion joints.

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A mathematical model for designing a reliable cellular hybrid manufacturing-remanufacturing system considering alternative and contingency process routings

SN Applied Sciences ◽

10.1007/s42452-021-04315-y ◽

2021 ◽

Vol 3 (3) ◽

Author(s):

Amirreza Hooshyar Telegraphi ◽

Akif Asil Bulgak

Keyword(s):

Mathematical Model ◽

Supply Chain ◽

Manufacturing Systems ◽

Closed Loop ◽

Sustainable Manufacturing ◽

Critical Issue ◽

Economic Benefits ◽

Mixed Integer ◽

Hybrid Manufacturing ◽

Closed Loop Supply Chain

AbstractDue to the stringent awareness toward the preservation and resuscitation of natural resources and the potential economic benefits, designing sustainable manufacturing enterprises has become a critical issue in recent years. This presents different challenges in coordinating the activities inside the manufacturing systems with the entire closed-loop supply chain. In this paper, a mixed-integer mathematical model for designing a hybrid-manufacturing-remanufacturing system in a closed-loop supply chain is presented. Noteworthy, the operational planning of a cellular hybrid manufacturing-remanufacturing system is coordinated with the tactical planning of a closed-loop supply chain. To improve the flexibility and reliability in the cellular hybrid manufacturing-remanufacturing system, alternative process routings and contingency process routings are considered. The mathematical model in this paper, to the best of our knowledge, is the first integrated model in the design of hybrid cellular manufacturing systems which considers main and contingency process routings as well as reliability of the manufacturing system.

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A truncated column generation algorithm for the parallel batch scheduling problem to minimize total flow time

European Journal of Operational Research ◽

10.1016/j.ejor.2020.03.044 ◽

2020 ◽

Vol 286 (2) ◽

pp. 432-443

Author(s):

Onur Ozturk

Keyword(s):

Column Generation ◽

Flow Time ◽

Batch Scheduling ◽

Scheduling Problem ◽

Total Flow ◽

Generation Algorithm ◽

Total Flow Time

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A STOCHASTIC BATCHING AND SCHEDULING PROBLEM

Probability in the Engineering and Informational Sciences ◽

10.1017/s0269964801154033 ◽

2001 ◽

Vol 15 (4) ◽

pp. 465-479 ◽

Cited By ~ 2

Author(s):

Ger Koole ◽

Rhonda Righter

Keyword(s):

Optimal Policy ◽

Semiconductor Manufacturing ◽

Processing Time ◽

Polynomial Time Algorithm ◽

Time Algorithm ◽

Flow Time ◽

Batch Scheduling ◽

Scheduling Problem ◽

Processing Times ◽

Deterministic Problem

We consider a batch scheduling problem in which the processing time of a batch of jobs equals the maximum of the processing times of all jobs in the batch. This is the case, for example, for burn-in operations in semiconductor manufacturing and other testing operations. Processing times are assumed to be random, and we consider minimizing the makespan and the flow time. The problem is much more difficult than the corresponding deterministic problem, and the optimal policy may have many counterintuitive properties. We prove various structural properties of the optimal policy and use these to develop a polynomial-time algorithm to compute the optimal policy.

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Performance optimization of a flexible manufacturing system using simulation: the Taguchi method versus OptQuest

SIMULATION ◽

10.1177/0037549718819804 ◽

2019 ◽

Vol 95 (11) ◽

pp. 1085-1096 ◽

Cited By ~ 1

Author(s):

Abdessalem Jerbi ◽

Achraf Ammar ◽

Mohamed Krid ◽

Bashir Salah

Keyword(s):

Taguchi Method ◽

Performance Optimization ◽

Flexible Manufacturing ◽

Manufacturing Systems ◽

Manufacturing System ◽

Flexible Manufacturing System ◽

Flow Time ◽

Mean Flow ◽

Taguchi Optimization ◽

Mean Flow Time

The Taguchi method is widely used in the field of manufacturing systems performance simulation and improvement. On the other hand, Arena/OptQuest is one of the most efficient contemporary simulation/optimization software tools. The objective of this paper is to evaluate and compare these two tools applied to a flexible manufacturing system performance optimization context, based on simulation. The principal purpose of this comparison is to determine their performances based on the quality of the obtained results and the gain in the simulation effort. The results of the comparison, applied to a flexible manufacturing system mean flow time optimization, show that the Arena/OptQuest optimization platform outperforms the Taguchi optimization method. Indeed, the Arena/OptQuest permits one, through the lowest experimental effort, to reliably minimize the mean flow time of the studied flexible manufacturing system more than the Taguchi method.

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An Efficient Batch Scheduling Model for Hospital Sterilization Services Using Genetic Algorithm

Research Anthology on Multi-Industry Uses of Genetic Programming and Algorithms ◽

10.4018/978-1-7998-8048-6.ch047 ◽

2021 ◽

pp. 928-946

Author(s):

Shubin Xu ◽

John Wang

Keyword(s):

Genetic Algorithm ◽

Medical Devices ◽

Programming Model ◽

Flow Time ◽

Nonlinear Integer Programming ◽

Batch Scheduling ◽

Scheduling Problem ◽

Work In Process ◽

Completion Times ◽

Sum Of Completion Times

A major challenge faced by hospitals is to provide efficient medical services. The problem studied in this article is motivated by the hospital sterilization services where the washing step generally constitutes a bottleneck in the sterilization services. Therefore, an efficient scheduling of the washing operations to reduce flow time and work-in-process inventories is of great concern to management. In the washing step, different sets of reusable medical devices may be washed together as long as the washer capacity is not exceeded. Thus, the washing step is modeled as a batch scheduling problem where washers have nonidentical capacities and reusable medical device sets have different sizes and different ready times. The objective is to minimize the sum of completion times for washing operations. The problem is first formulated as a nonlinear integer programming model. Given that this problem is NP-hard, a genetic algorithm is then proposed to heuristically solve the problem. Computational experiments show that the proposed algorithm is capable of consistently obtaining high-quality solutions in short computation times.

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