Appa Iyer Sivakumar

A bee colony optimization algorithm to job shop scheduling

In the face of globalization and rapidly shrinking product life cycle, manufacturing companies are trying different means to improve productivity through management of machine utilization and product cycle-time. Job shop scheduling is an important task for manufacturing industry in terms of improving machine utilization and reducing cycle-time. However, job shop scheduling is inherently a NP-hard problem with no easy solution. This paper describes a novel approach that uses the honey bees foraging model to solve the job shop scheduling problem. Experimental results comparing the proposed honey bee colony approach with existing approaches such as ant colony and tabu search are presented

A simulation based analysis of cycle time distribution, and throughput in semiconductor backend manufacturing

Abstract This paper presents a preliminary analysis of the relationship between selected input and output variables in semiconductor backend manufacturing system, using a data driven discrete event simulation model. This study is of interest and importance for a better understanding of the controllable input variables in an effort to reduce factory cycle time and distribution. Our analysis quantifies the effect of varying the input variables of lot release controls, heuristic machine dispatching rules, elimination of selected processes, material handling time, set-up time, and machine up time on selected output variables of throughput, cycle time and cycle time spread. Simulation model of a semiconductor site based in Singapore is used as the base case and the effects are quantified against the base model.

Synchronized scheduling of assembly and multi-destination air-transportation in a consumer electronics supply chain

The paper studies the problem of synchronizing air transportation and assembly manufacturing to achieve accurate delivery with minimized cost in a consumer electronics supply chain. The motivation for this study came from a major computer manufacturer in a consumer electronics industry that faces challenges in the final stages of delivery of a supply chain. The synchronization problem is decomposed and formulated as two sub-problems, i.e. a multi-destination air transportation allocation problem and an assembly-scheduling problem. The first sub-problem is formulated and solved as an integer linear programming problem. For the assembly-scheduling problem, two solution methodologies using the concepts of forward and backward scheduling are presented. Computational results indicate that the proposed methodologies can achieve considerable cost reduction compared with the existing methodology applied in industry.

Simulation-based scheduling for dynamic discrete manufacturing

A simulation-based real-time scheduling mechanism for dynamic discrete manufacturing is presented. Modified mean flow time performance for different scheduling approaches is compared through off-line simulation experiments, under dynamic manufacturing environments that are subject to disturbances such as machine breakdowns. These experimental results are used as reference indices for the real-time scheduling mechanism to select the better scheduling approaches for further evaluation based on the actual manufacturing conditions. Discrete-event simulation is used online to evaluate the selected approaches and the corresponding schedules to determine the best solution. The selected schedule is used until the deviation of actual performance from the estimated one exceeds a given limit, or when a major event occurs. A new simulation is then performed with the remaining operations to select a new schedule.

Scheduling of single stage assembly with air transportation in a consumer electronic supply chain

Consumer electronics supply chain being a booming industry with intensive competition, multinational organizations are rapidly moving towards global manufacturing networks to minimize the costs and improve delivery efficiency. The studies on modeling and scheduling of global supply chains in consumer electronics industry have lead to growing interests in recent years. In this paper, the problem of synchronized scheduling of assembly with air transportation to minimize delivery costs is addressed. The overall problem is decomposed into sub-problems viz., the air transportation allocation problem and assembly scheduling problem. The air transportation allocation problem is shown to have the structure of the regular transportation problem, while the assembly scheduling problem is shown to be NP-hard. We investigate the case of process delays in assembly for reasons such as machine breakdowns, shortages of materials, etc., and present a schedule repair heuristic. We evaluate the performance of the proposed heuristic with industry practice methods by testing the heuristics on randomly generated problems of size varying from 20 to 100 jobs.

An efficient new job release control methodology

This paper presents a new job release methodology: WIPLOAD Control (WIPLCtrl), which is a workload limited release methodology for the overall shop floor. The behaviour of WIPLCtrl is analyzed using the Markov process model of a transfer line system to observe the potential advantage of WIPLCtrl relative to the conventional measure of system workload using the WIP level. A simulation experiment is then conducted considering a simplified semiconductor wafer fabrication system. The performance of WIPLCtrl is compared with that of an open-loop release methodology and three other closed-loop workload limited release methodologies. A case study is also carried out by simulating a real-life wafer fabrication, considering the complexities and the distinguishing features of semiconductor manufacturing. The experimental results indicate that WIPLCtrl is an efficient job release methodology, capable of reducing both the mean and the standard deviation of the cycle time for a given throughput level. The performance ...

Simulation based multiobjective schedule optimization in semiconductor manufacturing

In semiconductor manufacturing, it requires more than one objective such as cycle time, machine utilization and due date accuracy to be kept in focus simultaneously, while developing an effective scheduling. In this paper, a near optimal solution, which is not inferior to any other feasible solutions in terms of all objectives, is generated with a combination of the analytically optimal and simulation based scheduling approach. First, the job shop scheduling problem is modeled using the discrete event simulation approach and the problem is divided in to simulation clock based lot selection sub-problems. Then, at each decision instant in simulated time, a Pareto optimal lot is selected using the various techniques to deal with multiobjective optimization such as weighted aggregation approach, global criterion method, minimum deviation method, and compromise programming. An illustration shows how these techniques work effectively in solving the multiobjective scheduling problem using discrete event simulation.

An inventory–routing problem with the objective of travel time minimization

In this paper, we consider an inventory–routing problem (IRP) in a large petroleum and petrochemical enterprise group. Compared to many other IRPs, the problem in this paper includes some special aspects due to the operational constraints, such as hours-of-service regulations of the company and the industry. Also, in some cases, it is more important to avoid stock out for any station, rather than purely focusing on transportation cost minimization. The objective is to minimize the maximum of the route travel time, which is not addressed in the literature so far. We present a tabu search algorithm to tackle the problem, which builds in an efficient and effective procedure to improve the search quality in each iteration. Moreover, lower bounds of reasonable sized problems, which are intractable in the formulated mathematical model by existing optimization software, are obtained via Lagrangian relaxation technique. Computational results indicate that the lower bounds are tight and the tabu search is capable of providing near optimal, close-to-lower-bound solutions in a computational time effective manner.

Complexities and algorithms for synchronized scheduling of parallel machine assembly and air transportation in consumer electronics supply chain

In this paper, we study the problem of synchronized scheduling of assembly and air transportation to achieve accurate delivery with minimized cost in consumer electronics supply chain. This problem was motivated by a major PC manufacturer in consumer electronics industry. The overall problem is decomposed into two sub-problems, which consist of an air transportation allocation problem and an assembly scheduling problem. The air transportation allocation problem is formulated as an integer linear programming problem with the objective of minimizing transportation cost and delivery earliness tardiness penalties. The assembly scheduling problem seeks to determine a schedule ensuring that the orders are completed on time and catch the flights such that the waiting penalties between assembly and transportation is minimized. The problem is formulated as a parallel machine scheduling problem with earliness penalties. The computational complexities of the two sub-problems are investigated. The air transportation allocation problem with split delivery is shown to be solvable. The parallel machine assembly scheduling problem is shown to be NP-complete. Simulated annealing based heuristic algorithms are presented to solve the parallel machine problem.

Using A Bee Colony Algorithm For Neighborhood Search In Job Shop Scheduling Problems

This paper describes a population-based approach that uses a honey bees foraging model to solve job shop scheduling problems. The algorithm applies an efficient neighborhood structure to search for feasible solutions and iteratively improve on prior solutions. The initial solutions are generated using a set of priority dispatching rules. Experimental results comparing the proposed honey bee colony approach with existing approaches such as ant colony, tabu search and shifting bottleneck procedure on a set of job shop problems are presented. The results indicate the performance of the proposed approach is comparable to other efficient scheduling approaches.