K. Raj Kumar and T.T. Narendran
Addresses the problem of sequencing a set of PCBs on a single assembling machine. Considers two objectives, namely minimizing tardiness and minimizing the set‐ups. Reduces…
Abstract
Addresses the problem of sequencing a set of PCBs on a single assembling machine. Considers two objectives, namely minimizing tardiness and minimizing the set‐ups. Reduces component change‐overs by exploiting the similarity between PCBs. Proposes a new measure to sequence the PCBs, taking care of both the objectives. Develops a heuristic for solving the bi‐criteria problem. The proposed method performs better than the existing heuristics for the comparable situation of sequencing in a single machine job‐shop.
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R. Shankar, P. Vijayaraghavan and T. Narendran
Customer support assumes strategic importance in India for branded IT‐hardware products. An authorized service center and a stream of specialized service centers undertake field…
Abstract
Purpose
Customer support assumes strategic importance in India for branded IT‐hardware products. An authorized service center and a stream of specialized service centers undertake field services and represent a sale‐territory's support network. “Time constrained” service men have to deliver customized service meeting a promised time‐standard. The stochastic demand for support services severely mars the customer response resulting in poor service quality. A manufacturer has to address the following decisions under these conditions: what is the ideal staffing level in a territory considering restricted server availability? What will be the impact of changing the staffing levels on customer service level? This study develops an analytical model to address these decisions.
Design/methodology/approach
The study identifies the variables underlying stochastic service demand through a field survey and determines the demand distribution. Applying stochastic principles the study derives relation between field staffing level and customer response considering server time constraint. Study performs statistical analysis to validate this model with real time data on variables collected from the field survey.
Findings
The outcomes of analysis reveal the following findings: this model can be applied in service systems where a time constrained server has to deliver expected level of performance (research implication); and increasing field staffing levels obscures the significant difference between the customer waiting times under very high levels of uncertain demand (practical implication).
Originality/value
The study derives relation between the staffing levels and customer waiting time considering uncertain demand with restricted working hour conditions.
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Muna Ezzi Raypah, Shahrom Mahmud, Mutharasu Devarajan and Anoud AlShammari
Optimization of light-emitting diodes’ (LEDs’) design together with long-term reliability is directly correlated with their photometric, electric and thermal characteristics. For…
Abstract
Purpose
Optimization of light-emitting diodes’ (LEDs’) design together with long-term reliability is directly correlated with their photometric, electric and thermal characteristics. For a given thermal layout of the LED system, the maximum luminous flux occurs at an optimal electrical input power and can be determined using a photo-electro-thermal (PET) theory. The purpose of this study is to extend the application of the luminous flux equation in PET theory for low-power (LP) LEDs.
Design/methodology/approach
LP surface-mounted device LEDs were mounted on substrates of different thermal resistances. Three LEDs were attached to substrates which were flame-retardant fiberglass epoxy (FR4) and two aluminum-based metal core printed circuit boards (MCPCBs) with thermal conductivities of about 1.0 W/m.K, 2.0 W/m.K and 5.0 W/m.K, respectively. The conjunction of thermal transient tester and thermal and radiometric characterization of LEDs system was used to measure the thermal and optical parameters of the LEDs at a certain range of input current and temperature.
Findings
The validation of the extended application of the luminous flux equation was confirmed via a good agreement between the practical and theoretical results. The outcomes show that the optimum luminous flux is 25.51, 31.91 and 37.01 lm for the LEDs on the FR4 and the two MCPCBs, respectively. Accordingly, the stipulated maximum electrical input power in the LED datasheet (0.185 W) is shifted to 0.6284, 0.6963 and 0.8838 W between the three substrates.
Originality/value
Using a large number of LP LEDs is preferred than high-power (HP) LEDs for the same system power to augment the heat transfer and provide a higher luminous flux. The PET theory equations have been applied to HP LEDs using heatsinks with various thermal resistances. In this work, the PET theory luminous flux equation was extended to be used for Indium Gallium Aluminum Phosphide LP LEDs attached to the substrates with dissimilar thermal resistances.
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The purpose of this paper is to outline the main features concerning the optimization of printed circuit board (PCB) fabrication by improving the manufacturing process…
Abstract
Purpose
The purpose of this paper is to outline the main features concerning the optimization of printed circuit board (PCB) fabrication by improving the manufacturing process productivity.
Design/methodology/approach
The author explored two different approaches to increase the manufacturing process productivity of PCBs. The first approach involved optimization of the PCB manufacturing process as a whole. The second approach was based on increasing the process productivity at the operational level.
Findings
To reduce the total manufacturing time, two heuristic algorithms for solving flowshop scheduling problems were designed. These algorithms were used for the computation of an optimal PCB manufacturing schedule. The case study shows both mono‐ and bi‐criteria optimization of the PCBs manufacturing.
Research limitations/implications
While the input data used in the case study were based on random numbers, the mathematical considerations drew only the main directions for manufacturing process optimization.
Originality/value
The paper shows two original heuristic algorithms for solving the flowshop scheduling problem, with high performance according to the best heuristics in the field. Besides their performances, these algorithms have the advantage of simplicity and ease of implementation on a computer. Using these algorithms, the optimal schedule for the PCB manufacturing process was calculated. For the case of the bi‐criteria optimization, the study of points which belong to the Pareto‐optimal set are presented.
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Wei‐Shing Chen and Chiuh‐Cheng Chyu
This paper considers the decision problem for a minimum setup strategy of a production system arising in the assembly of printed circuit boards of different types, using a…
Abstract
This paper considers the decision problem for a minimum setup strategy of a production system arising in the assembly of printed circuit boards of different types, using a placement machine with multi‐slot feeders. We formulate the problem as a binary linear programming model, and propose a heuristic procedure to find the solution that consists of a board‐assembly sequence, an associated component loading and unloading strategy and a feeder‐assignment plan within reasonable computational effort. Computational results from solving the simulated problem instances by using the heuristic method and the mathematical model are provided and compared. The proposed heuristic procedure can be incorporated into the PCB scheduling optimization software to decrease cycle times and increase overall assembly throughput in a high‐mix, low‐volume PCB manufacturing environment.
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Wei‐Shing Chen and Chiuh‐Cheng Chyu
In a high‐mix middle‐volume production environment for printed circuit board (PCB) assembly, the production efficiency strongly depends not only on the tactical level of how to…
Abstract
In a high‐mix middle‐volume production environment for printed circuit board (PCB) assembly, the production efficiency strongly depends not only on the tactical level of how to group PCBs but also on the operational level of how to assign feeders and determine placement sequences in the group setup strategy. The present study discusses the problem of clustering PCBs into groups in such a way that total placement and setup time can be minimized. This problem is motivated by a situation that the reduction of group setup‐time and efficiency loss of placement time should be balanced in a PCB group setup optimization. This research incorporates placement time into the PCB job grouping and presents a weighting similarity measure. To solve component‐feeder assignment and placement sequences for a family of PCBs, an efficient procedure based upon an ant colony optimization (ACO) algorithm is developed. Group setup performance is evaluated and compared under a variety of grouping algorithms. Experiments are conducted to discover situations where the consideration of efficiency loss of placement time can make a significant improvement in PCB group assembly.
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Murtadha Aldoukhi and Surendra M. Gupta
This chapter proposes a multiobjective model to design a Closed Loop Supply Chain (CLSC) network. The first objective is to minimize the total cost of the network, while the…
Abstract
This chapter proposes a multiobjective model to design a Closed Loop Supply Chain (CLSC) network. The first objective is to minimize the total cost of the network, while the second objective is to minimize the carbon emission resulting from production, transportation, and disposal processes using carbon cap and carbon tax regularity policies. In the third objective, we maximize the service level of retailers by using maximum covering location as a measure of service level. To model the proposed problem, a physical programming approach is developed. This work contributes to the literature in designing an optimum CLSC network considering the service level objective and product substitution.
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Adil Baykasog¯lu, Nabil N.Z. Gindy and Richard C. Cobb
An integer multiple objective non‐linear mathematical programming formulation is developed for simultaneously forming part/machine cells. In the proposed model, generic capability…
Abstract
An integer multiple objective non‐linear mathematical programming formulation is developed for simultaneously forming part/machine cells. In the proposed model, generic capability units which are termed as resource elements are used to define the processing requirements of parts and processing capabilities of machine tools. Machine capabilities are not generally taken into account in the previous cell formation procedures. Explicit consideration of unique and overlapping machine capabilities can result in better manufacturing cell designs with higher utilisation levels and less machine duplication. The proposed cell formation model has distinguishing features. Several important cell formation objectives, such as minimisation of part dissimilarity (based on production requirements and processing sequences of parts) in formed cells, minimisation of cell load imbalance, and minimisation of extra capacity requirements for cell formation, are considered. In order to solve the mathematical programming model, a simulated annealing algorithm is developed. Cooperative game theoretic approach is applied for evaluating multiple objectives.
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Grouping parts into families which can be produced by a cluster of machine cells is the cornerstone of cellular manufacturing, which in turn is the building block for flexible…
Abstract
Grouping parts into families which can be produced by a cluster of machine cells is the cornerstone of cellular manufacturing, which in turn is the building block for flexible manufacturing systems. Cellular manufacturing is a group technology (GT) concept that has recently attracted the attention of manufacturing firms operating in a jobshop environment to consider redesigning their manufacturing systems so as to take advantage of increased throughput, and reductions in work‐in‐progress, set‐up time, and lead times; leading to product quality and customer satisfaction. Presents a similarity order clustering technique for the machine cell formation problem. The procedure is compared with many existing procedures using eight well‐known problems from the literature. The results show that the proposed procedure, which is attractive due to its simplicity, compares well with existing procedures and should be useful to practitioners and researchers.
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Saeed Zolfaghari and Ming Liang
The solution quality of a comprehensive machine/part grouping problem, where the processing times, lot sizes and machine capacities are considered, may not be properly evaluated…
Abstract
The solution quality of a comprehensive machine/part grouping problem, where the processing times, lot sizes and machine capacities are considered, may not be properly evaluated using a binary performance measure. This paper suggests a generalized grouping efficacy index which has been compared favorably with two binary performance measures. A genetic algorithm using the generalized performance measure as the objective is developed to solve the comprehensive grouping problems. The algorithm has been tested using a number of reference problems with processing times being randomly assigned to all operations. The effects of three major genetic parameters (population size, mutation rate and the number of crossover points) have also been examined. The results indicate that, when the computational time is fixed, larger population size and lower mutation rate tend to improve solution quality while the number of crossover points has no significant impact on the final solution.