Due to increasing penetration of internet connectivity, on-line retail is growing from the pioneer phase to increasing integration within people & apos; s lives and companies & apos; normal business practices. In the increasingly competitive environment, on-line retail service providers require systematic and structured approach to have cutting edge over the rival. Thus, the use of benchmarking has become indispensable to accomplish superior performance to support the on-line retail service providers. This paper uses the fuzzy analytic hierarchy process (FAHP) approach to support a generic on-line retail benchmarking process. Critical success factors for on-line retail service have been identified from a structured questionnaire and literature and prioritized using fuzzy AHP. Using these critical success factors, performance levels of the ORENET an on-line retail service provider is benchmarked along with four other on-line service providers using TOPSIS method. Based on the benchmark, their relative ranking has also been illustrated.

In this work, Taguchi method is applied to determine the optimum process parameters for turning of AISI 304 austenitic stainless steel on CNC lathe. A Chemical vapour deposition (CVD) coated cemented carbide cutting insert is used which is produced by DuratomicTM technology of 0.4 and 0.8 mm nose radii. The tests are conducted at four levels of Cutting speed, feed and depth of cut. The influence of these parameters are investigated on the surface roughness and material removal rate (MRR). The Analysis Of Variance (ANOVA) is also used to analyze the influence of cutting parameters during machining. The results revealed that cutting speed significantly (46.05%) affected the machined surface roughness values followed by nose radius (23.7%). The influence of the depth of cut (61.31%) in affecting material removal rate (MRR) is significantly large. The cutting speed (20.40%) is the next significant factor. Optimal range and optimal level of parameters are also predicted for responses.

Globalization has put fierce competition for manufacturing managers in terms of flexibility, smaller lead times, competitive costs, etc. To attain these capabilities, manufacturing managers are taking heedless decisions for investing in advanced manufacturing technologies, without measuring their actual effectiveness for their organisations. There is a need to measure the effectiveness of manufacturing systems to make better future policies and investment planning. This paper provides a comprehensive bibliography on the techniques and their rationale in the effectiveness measurement of advanced manufacturing systems. The paper cites 265 articles from a variety of published sources. The list contains published research mainly from 1990 to 2012 and a selected published work prior to 1990.

In general, production system often gets disrupted due to uncertainty and un-planned events, which also affect demands resulting in less abet-margin of a company. With disrupted production system, management would need to study the variation of demand pattern and disruption of system; we have attempted an effort to establish an exponential demand with the production system and solved analytically the problem to determine production time before and after disruptions. Exponentially demand pattern studied, and also we simulate for sensitivity analysis in order to find which parameter is getting significant change for the proposed model.

In this paper, we study no-wait flow shop problem where setup times depend on sequence of operations. The proposed problem considers sequence-independent removal times, release date with an additional assumption that there are some preliminary setup times. There are two objectives of weighted mean tardiness and makespan associated with the proposed model of this paper. We formulate the resulted problem as a mixed integer programming, where a two-phase fuzzy programming is implemented to solve the model. To examine the performance of the proposed model, we generate several sample data, randomly and compare the results with other methods. The preliminary results indicate that the proposed two-phase model of this paper performed relatively better than Zimmerman & apos; s single-phase fuzzy method.

This paper addresses the scheduling of machines, an Automated Guided Vehicle (AGV) and two robots in a Flexible Manufacturing System (FMS) formed in three loop layouts, with objectives to minimize the makespan, mean flow time and mean tardiness. The scheduling optimization is carried out using Sheep Flock Heredity Algorithm (SFHA) and Artificial Immune System (AIS) algorithm. AGV is used for carrying jobs between the Load/Unload station and the machines. The robots are used for loading and unloading the jobs in the machines, and also used for transferring jobs between the machines. The algorithms are applied for test problems taken from the literature and the results obtained using the two algorithms are compared. The results indicate that SFHA performs better than AIS for this problem.

To acquire the competitive advantages in order to survive in the global business scenario, modern companies are now facing the problems of selecting key supply chain strategies. Strategy selection becomes difficult as the number of alternatives and conflicting criteria increases. Multi criteria decision making (MCDM) methodologies help the supply chain managers take a lead in a complex industrial set-up. The present investigation applies fuzzy MCDM technique entailing multi-objective optimization on the basis of ratio analysis (MOORA) in selection of alternatives in a supply chain. The MOORA method is utilized to three suitable numerical examples for the selection of supply chain strategies (warehouse location selection and vendor/supplier selection). The results obtained by using current approach almost match with those of previous research works published in various open journals. The empirical study has demonstrated the simplicity and applicability of this method as a strategic decision making tool in a supply chain.

This paper considers an economic lot and delivery scheduling problem (ELDSP) in a fuzzy environment with the fuzzy shelf life for each product. This problem is formulated in a flexible job shop with unrelated parallel machines, when the planning horizon is finite and it determines lot sizing, scheduling and sequencing, simultaneously. The proposed model of this paper is based on the basic period (BP) approach. In this paper, a mixed-integer nonlinear programming (MINLP) model is presented and then it is changed into two models in the fuzzy shelf life. The main model is dependent to the multiple basic periods and it is difficult to solve the resulted proposed model for large-scale problems in reasonable amount of time; thus, an efficient heuristic method is proposed to solve the problem. The performance of the proposed model is demonstrated using some numerical examples.

The increase competition and decline economy has increased the relevant importance of having reliable supply chain. The primary objective of many supply chain problems is to reduce the cost of services and, at the same time, to increase the quality of services. In this paper, we present a multi-level supply chain network by considering multi products, single resource and deterministic cost and demand. The proposed model of this paper is formulated as a mixed integer programming and we present two metaheuristics namely MOPSO and NSGA-II to solve the resulted problems. The performance of the proposed models of this paper has been examined using some randomly generated numbers and the results are discussed. The preliminary results indicate that while MOPSO is able to generate more Pareto solutions in relatively less amount of time, NSGA-II is capable of providing better quality results.

In a previously published paper by Khan et al. (2011) [Khan, M., Jaber, M.Y., & Bonney M. (2011). An economic order quantity (EOQ) for items with imperfect quality and inspection errors, International Journal of Production Economics, 133, 113-118], we found that there is a contradiction between the cycle length and the holding cost per cycle. To obtain the cycle length, the authors assumed that the returned items from the market were replaced with good quality items. However, for the holding cost per cycle, the authors implicitly assumed that the returned items were not replaced by good quality items. In this note, we first point out the contradiction. Then we fix this flaw and develop a corrected EOQ.