Scheduling of Batch Processors in Semiconductor Manufacturing – A Review

In this paper a review on scheduling of batch processors (SBP) in semiconductor manufacturing (SM) is presented. It classifies SBP in SM into 12 groups. The suggested classification scheme organizes the SBP in SM literature, summarizes the current research results for different problem types. The classification results are presented based on various distributions and various methodologies applied for SBP in SM are briefly highlighted. A comprehensive list of references is presented. It is hoped that, this review will provide a source for other researchers/readers interested in SBP in SM research and help simulate further interest.Singapore-MIT Alliance (SMA

Importance of Technological Innovation for SME Growth: Evidence from India

This paper probes the drivers, dimensions, achievements, and outcomes of technological innovations carried out by SMEs in the auto components, electronics, and machine tool sectors of Bangalore in India. Further, it ascertains the growth rates of innovative SMEs vis-à-vis non-innovative SMEs in terms of sales turnover, employment, and investment. Thereafter, it probes the relationship between innovation and growth of SMEs by (i) estimating a correlation between innovation sales and sales growth, (ii) calculating innovation sales for high, medium, and low growth innovative SMEs and doing a aggregate one-way ANOVA, and (iii) ascertaining the influence of innovation sales, along with investment growth and employment growth on gross value-added growth by means of multiple regression analysis. The paper brings out substantial evidence to argue that innovations of SMEs contributed to their growth.Technological innovations, sales growth, auto components, electronics, machine tools, Bangalore

Experimental Analysis of Some Variants of Vogel’s Approximation Method.

This paper presents a variant of Vogel's approximation method (VAM) for transportation problems. The importance of determining efficient solutions for large sized transportation problems is borne out by many practical problems in industries, the military, etc. With this motivation, a few variants of VAM incorporating the total opportunity cost (TOC) concept were investigated to obtain fast and efficient solutions. Computational experiments were carried out to evaluate these variants of VAM. The quality of solutions indicates that the basic version of the VAM coupled with total opportunity cost (called the VAM-TOC) yields a very efficient initial solution. In these experiments, on an average, about 20% of the time the VAM-TOC approach yielded the optimal solution and about 80% of the time it yielded a solution very close to optimal (0.5% loss of optimality). The CPU time required for the problem instances tested was very small (on an average, less than 10s on a 200MHz Pentium maxjhine with 64MB RAM)

Transport analytics in action: a cloud-based decision support system for efficient city bus transportation

Optimising city bus transport operations helps conserve fuel by providing the urban transport service as efficiently as possible. This study develops a Cloud-based Decision Support System (C-DSS) for transport analytics. The C-DSS is based on an intelligent model on location of depots for opening new depots and/or closing a few existing depots and allocation of city-buses to depots. The C-DSS is built on the Cloud Computing architecture with three layers and includes an efficient and simple greedy heuristic algorithm. Using modern information and communications technology tools, the proposed C-DSS minimizes the cost of city bus transport operations and in turn to reduce fuel consumption and CO2 emissions in urban passenger transport. The proposed C-DSS is demonstrated for its workability and evaluated for its performance on 25 large scale pseudo data generated based on the observation from Bangalore Metropolitan Transport Corporation (BMTC) in India

Scheduling identical parallel machines with machine eligibility restrictions to minimize total weighted flowtime in automobile gear manufacturing

In this paper, we address a scheduling problem for minimizing total weighted flowtime, observed in automobile gear manufacturing. Specifically, the bottleneck operation of the pre-heat treatment stage of gear manufacturing process has been dealt with in scheduling. Many real-life scenarios like unequal release times, sequence dependent setup times, and machine eligibility restrictions have been considered. A mathematical model taking into account dynamic starting conditions has been proposed. The problem is derived to be NP-hard. To approach the problem, a few heuristic algorithms have been proposed. Based on planned computational experiments, the performance of the proposed heuristic algorithms is evaluated: (a) in comparison with optimal solution for small-size problem instances and (b) in comparison with the estimated optimal solution for large-size problem instances. Extensive computational analyses reveal that the proposed heuristic algorithms are capable of consistently yielding near-statistically estimated optimal solutions in a reasonable computational time

Minimizing total weighted tardiness on heterogeneous batch processors with incompatible job families

In this paper, we address a scheduling problem for minimizing total weighted tardiness. The background for the paper is derived from the automobile gear manufacturing process. We consider the bottleneck operation of heat treatment stage of gear manufacturing. Real-life scenarios like unequal release times, incompatible job families, nonidentical job sizes, heterogeneous batch processors, and allowance for job splitting have been considered. We have developed a mathematical model which takes into account dynamic starting conditions. The problem considered in this study is NP-hard in nature, and hence heuristic algorithms have been proposed to address it. For real-life large-size problems, the performance of the proposed heuristic algorithms is evaluated using the method of estimated optimal solution available in literature. Extensive computational analyses reveal that the proposed heuristic algorithms are capable of consistently obtaining near-optimal statistically estimated solutions in very reasonable computational time

Experimental investigation for performance assessment of scheduling policies in semiconductor wafer fabrication-a simulation approach

This paper is concerned with assessing the impact of 15 existing release policies in combination with three dispatching rules (together called as scheduling policy) on the performance of semiconductor fabrication facilities using a simulation model of a representative but fictitious semiconductor wafer fab. The performance criteria employed includes average cycle time, standard deviation of cycle time, work in process (WIP) level, and throughput. Arena simulation software is used to build the simulation model and conduct the experimental study. The experimental results indicate that workload regulating (WR), constant work in process (CONWIP), and constant load (CONLOAD) policies are superior among tested release policies and shortest remaining processing time (SRPT) is the best dispatching rule. This paper present a new release policy called as constant workload (CONSTWL), which is a modified version of CONWIP policy to overcome the limitations of traditional release policies. CONSTWL policy triggers the release of job into the system based on the overall workload of shop floor. Results on computational experiments indicate that CONSTWL outperforms traditional release policies in terms of the average cycle time, the standard deviation of cycle time and work in process under a prescribed throughput level. The positive impact of CONSTWL policy on system performance appears to be reliable with the increase of system congestion level. CONSTWL policy may prove useful in practical contexts of make to stock manufacturing environment whose orders are met usually from finished inventory