Proactive inventory policy intervention to mitigate risk within cooperative supply chains
, Available Online, November 27
Takako Kurano, Kenneth N. McKay and Gary W. Black PDF (256K)
Abstract: This exploratory paper will investigate the concept of supply chain risk management involving supplier monitoring within a cooperative supply chain. Inventory levels and stockouts are the key metrics. Key to this concept is the assumptions that (1) out-of-control supplier situations are causal triggers for downstream supply chain disruptions, (2) these triggers can potentially be predicted using statistical process monitoring tools, and (3) carrying excess inventory only when needed is preferable as opposed to carrying excess inventory on a continual basis. Simulation experimentation will be used to explore several supplier monitoring strategies based on statistical runs tests, specifically "runs up and down" and/or "runs above and below" tests. The sensitivity of these tests in detecting non-random supplier behavior will be explored and their performance will be investigated relative to stock-outs and inventory levels. Finally, the effects of production capacity and yield rate will be examined. Results indicate out-of-control supplier signals can be detected beforehand and stock-outs can be significantly reduced by dynamically adjusting inventory levels. The largest benefit occurs when both runs tests are used together and when the supplier has sufficient production capacity to respond to downstream demand (i.e., safety stock) increases. When supplier capacity is limited, the highest benefit is achieved when yield rates are high and, thus, yield loss does not increase supplier production requirements beyond its available capacity.
Keywords: Supply chain risk management; Dynamic inventory policy; Cooperative supply chain; Simulation and supply chains; Simulation and risk management
Modeling the effect of variable work piece hardness on surface roughness in an end milling using multiple regression and adaptive Neuro fuzzy inference system
, Available Online, November 26
Purushottam S. Desale, and Ramchandra S. Jahagirdar PDF (256K)
Abstract: The aim of this study is to correlate work piece material hardness with surface roughness in prediction studies. The proposed model is for prediction of surface roughness of tool steel materials of hardness 55 HRC to 62 HRC (±2 HRC). The machining experiments are performed under various cutting conditions using work piece of different hardness. The surface roughness of these specimens is measured. The result showed that the influence of work piece material hardness on surface finish is significant for cutting speed and feed in CNC end milling operation. It is also observed that the surface roughness prediction accuracy of Adaptive neuro fuzzy inference system using triangular membership function is better than Gaussian, bell shape membership function and regression analysis. Surface roughness prediction accuracy with material hardness as input parameter is 97.61%.
Keywords: End Milling; Tool steel; Surface roughness; Fuzzy inference system; Regression
Job shop scheduling with makespan objective: A heuristic approach
, Available Online, November 22
Mohsen Ziaee PDF (256K)
Abstract: Job shop has been considered as one of the most challenging scheduling problems and there are literally tremendous efforts on reducing the complexity of solution procedure for solving job shop problem. This paper presents a heuristic method to minimize makespan for different jobs in a job shop scheduling. The proposed model is based on a constructive procedure to obtain good quality schedules, very quickly. The performance of the proposed model of this paper is examined on standard benchmarks from the literature in order to evaluate its performance. Computational results show that, despite its simplicity, the proposed heuristic is computationally efficient and practical approach for the problem.
Keywords: Scheduling; Job shop; Makespan; Heuristic
Inventory control with deteriorating items: A state-of-the-art literature review
, Available Online, November 18
Narges Khanlarzade, Babak Yousefi Yegane, Isa Nakhai Kamalabadi and Hiwa Farughi PDF (256K)
Abstract: The present study reviews different studies on inventory control of deteriorating items in chain supply published over the period 1963- 2013. The study investigates supply chain of the items in terms of various perspectives. Finally, the summary of the studies is shown in two tables for one-echelon and multi-echelon supply chain including the main information and assumptions of each paper. In the mentioned tables, the papers were classified in terms of the type of demand rate, deterioration rate, solution procedure and findings. It can be said that no analysis on the results was done in the present study and it can be only used as a good reference in the study field for other researchers.
Keywords: One-echelon supply chain; Multi-echelon supply chain; Deteriorating items; Inventory control
Scheduling algorithm with controllable train speeds and departure times to decrease the total train tardiness
, Available Online, November 17
Omid Gholami and Yuri N. Sotskov PDF (256K)
Abstract: The problem of generating a train schedule for a single-track railway system is addressed in this paper. A three stage scheduling is proposed to reduce the total train tardiness. We derived an appropriate job-shop scheduling algorithm called DR-algorithm. In the first stage, by determining appropriate weights of the dispatching rules, a pre-schedule is constructed. In the second stage, on the basis of the pre-schedule, the departure times of the trains are modified to reduce the number of conflicts in using railway sections by different trains. In the third stage, a train speed control helps the scheduler to change the trains’ speeds in order to reduce the train tardiness and to reach other objectives. The factual train schedule is based on the modified train speeds and on the modified departure times of the trains. The experimental running of the DR-algorithm on the benchmark instances showed this algorithm can solve train scheduling problems in a close to optimal way. In particular, the total train tardiness was reduced about 20% due to controlling train speeds and the departure times of the trains.
Keywords: Train timetabling; Job-shop scheduling; Makespan; Total tardiness; Dispatching rules
Application of Taguchi and regression analysis on surface roughness in machining hardened AISI D2 steel
, Available Online, November 15
Ashok Kumar Sahoo PDF (256K)
Abstract: The objective of the study is to assess the performance of multilayer coated carbide insert in the machining of hardened AISI D2 steel (53 HRC) using Taguchi design of experiment. The experiment was designed based on Taguchi L27 orthogonal array to predict surface roughness. The S/N ratio and optimum parametric condition are analysed. The analysis of variance has also been carried out to predict the significant factors affecting surface roughness. Based on Taguchi S/N ratio and ANOVA, feed is the most influencing parameter for surface roughness followed by cutting speed whereas depth of cut has least significant from the experiments. In regression model, the value of R2 being 0.98 indicates that 98 % of the total variations are explained by the model. It indicates that the developed model can be effectively used to predict the surface roughness on the machining of D2 steel with 95% confidence intervals.
Keywords: Coated carbide; Taguchi; Surface roughness; ANOVA; Regression
An economic production model for time dependent demand with rework and multiple production setups
, Available Online, October 30
S.R. Singh, Shalini Jain and S. Pareek PDF (256K)
Abstract: In this paper, we present a model for time dependent demand with multiple productions and rework setups. Production is demand dependent and greater than the demand rate. Production facility produces items in m production setups and one rework setup (m, 1) policy. The major reason of reverse logistic and green supply chain is rework, so it reduces the cost of production and other ecological problems. Most of the researchers developed a rework model without deteriorating items. A numerical example and sensitivity analysis is shown to describe the model.
Keywords: Production models; Time dependent demand; Multiple production setups; Rework
Flexible manufacturing system selection using preference ranking methods : A comparative study
, Available Online, October 25
Prasenjit Chatterjee and Shankar Chakraborty PDF (256K)
Abstract: Flexible manufacturing systems (FMSs) offer opportunities for the manufacturers to improve their technology, competitiveness and profitability through a highly efficient and focused approach to manufacturing effectiveness. Justification, evaluation and selection of FMSs have now been receiving significant attention in the manufacturing environment. Evaluating alternative FMSs in the presence of multiple conflicting criteria and performance measures is often a difficult task for the decision maker. Preference ranking tools are special types of multi-criteria decision-making methods in which the decision maker’s preferences on criteria are aggregated together to arrive at the final evaluation and selection of the alternatives. This paper deals with the application of six most potential preference ranking methods for selecting the best FMS for a given manufacturing organization. It is observed that although the performances of these six methods are almost similar, ORESTE (Organization, Rangement Et Synthese De Donnes Relationnelles) method slightly outperforms the others. These methods use some preference function or utility value or Besson ranking of criteria and alternatives, to indicate how much an alternative is preferred to the others. Most of these methods need quantification of criteria weights or different preference parameters, but ORESTE method, being an ordinal outranking approach, only requires ordinal data and attribute rankings according to their importance. Therefore, it is particularly applicable to those situations where the decision maker is unable to provide crisp evaluation data and attribute weights.
Keywords: Flexible manufacturing system; Multi-criteria decision-making; Preference ranking method; Ranking
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