In this paper, a comparison is presented between two prime methods of producing prosthetic sockets by using the fuzzy linguistic hedges approach on the qualitative feedback of Indian prosthetic users. Recent trends indicate that the Indian manufacturers have tried to adopt the newer technologies like reverse engineering (RE) approach to achieve the desired goals. However, the satisfaction of the user is of utmost importance for the unique and customized products for rehabilitation. In order to analyze the effectiveness of the manufacturing approaches, user case studies are taken, based on the linguistic feedbacks, and a comparative study is conducted. Thirteen users from four different manufacturing units are taken for study and sockets made by conventional as well as RE are experimented. Fuzzy membership functions are constructed using the linguistic hedges based on the user feedbacks. An analytical hierarchy process (AHP) is applied to arrive at a decision to select the manufacturing process for user satisfaction and manufacturing excellence.

Selection of suitable weapon for armed forces is one of the most complex decisions, which must be taken by martial administrators. The procedure of decision making on weapon selection is integrated with various criteria, which are often in conflict. This paper presents a multi criteria decision making problem based on the implementation of ELECTRE III technique. The proposed model compares all acceptable choices based on a systematic and sophisticated procedure and provides some efficient solutions. The implementation of the proposed model is demonstrated for an infantry rifle selection. The proposed model, first, determines acceptable choices and criteria through Simos method and then it uses ELECTRE III to rank various alternatives. The result of the application of the proposed model for a real-world case study of choosing an infantry rifle indicates its effectiveness.

Product mix problem is one of the most important decisions made in production systems. Several algorithms have been developed to determine the product mix. Most of the previous works assume that all resources can perform, simultaneously and independently, which may lead to infeasibility of the schedule. In this paper, product mix problem and scheduling are considered, simultaneously. A new mixed-integer programming (MIP) model is proposed to formulate this problem. The proposed model differentiates between process batch size and transfer batch size. Therefore, it is possible to have overlapped operations. The numerical example is used to demonstrate the implementation of the proposed model. In addition, the proposed model is examined using some instances previously cited in the literature. The preliminary computational results show that the proposed model can generate higher performance than conventional product mix model.

The aversion dynamics research agenda has incorporated within dispatching heuristics a number of real-world observations involving risk mitigation practices used by real schedulers. One such observation is that schedulers occasionally offload risky jobs from a primary machine to otherwise less desirable machine (older, slower) during periods of peak load to avoid the effects the risky job can have on subsequent jobs. This paper examines this situation within the proportional parallel machine environment. Safety time is used to adjust dispatching priorities of risky jobs to reflect the aversion. The effect of various safety time values on performance is studied. Robust safety time values and/or intervals are identified across a variety of experimental factors related to risk level, percent risky jobs in the job stream, and due date distribution.

Reviewing the evolutionary trend of the models used in design and development of mechatronic products reveals the necessity for integration of the design characteristics and requirements in various engineering fields. Such products should agilely embrace rapid, persistent and complex requirements in competitive environments. This research aims to develop an integrated model for designing and developing mechatronic products within the context of agile production system. The study tries to eliminate unnecessary stages of design and simulation of products and increase the number of tested ideas. This suggests a distinction between product innovation and product improvement cycles and thus makes employing a pre-active approach to responding possible. Since the term “mechatronic products” is often used interchangeably with “robots”, one of the most commonly used types of them, i.e. tracer robot is considered as the statistical population for the proposed study. By choosing experimental (laboratory) research method, two categories of tracer robots are created: the tracer robots based on the V-model as the only integrated existing model and the robots based on the W-model as the model proposed by this study with a sample size of 35 sets in each group. The results indicate that both method provide acceptable validity although one model seems to perform better than the other one.

Nature inspired population based algorithms is a research field which simulates different natural phenomena to solve a wide range of problems. Researchers have proposed several algorithms considering different natural phenomena. Teaching-Learning-based optimization (TLBO) is one of the recently proposed population based algorithm which simulates the teaching-learning process of the class room. This algorithm does not require any algorithm-specific control parameters. In this paper, elitism concept is introduced in the TLBO algorithm and its effect on the performance of the algorithm is investigated. The effects of common controlling parameters such as the population size and the number of generations on the performance of the algorithm are also investigated. The proposed algorithm is tested on 35 constrained benchmark functions with different characteristics and the performance of the algorithm is compared with that of other well known optimization algorithms. The proposed algorithm can be applied to various optimization problems of the industrial environment.

We establish a robust FLOWSORT-based tool to sort mutual funds with respect to process-oriented social responsibility and recommend the use of limiting profiles with open classes. The tool provides an alternative for the limited dichotomous classification of funds, i.e. socially responsible investing (SRI) versus conventional funds. By allowing for more heterogeneity in social responsibility the sorting tool is promising for scholars to improve fund performance measurements, and useful for governments to better regulate the supply of SRI products.

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.