Non-traditional machining (NTM) refers to a variety of thermal, chemical, electrical and mechanical material removal processes, developed to generate complex and intricate shapes in advanced engineering materials with high strength-to-weight ratio. Selection of the optimal NTM process for generating a desired feature on a given material requires the consideration of several factors among which the type of the work material and shape to be machined are the most significant ones. Presence of a large number of NTM processes along with their complex characteristics and capabilities, and lack of experts in NTM process selection domain compel for development of a structured approach for NTM process selection for a given machining application. Thus, the objective of this paper is set to develop a decision-making model in Visual BASIC 6.0 to automate the NTM process selection procedure with the help of graphical user interface and visual decision aids. It is also integrated with quality function deployment technique to correlate the customers’ requirements (product characteristics) with technical requirements (process characteristics). Four illustrative examples are also provided to demonstrate the potentiality of the developed model in solving NTM process selection problems.

Over time, the number of unexpected earthy, oceanic and atmospheric events is rising each year. Hence, disaster management is considered as one of the most important scientific and practical issues in developed and developing countries. Therefore, in this study, we review and develop the problem of locating the emergency units with constraints including the number of available ambulances, limited budget for deployment of ambulances and the minimum acceptable level of covering. The proposed model improves the spatial queuing model (SQM) and Maximal Covering Location Problem (MCLP) by considering the cost of the deployment of the emergency units, which makes it closer to real-world conditions. Because the proposed model is NP-hard, the model is solved using three heuristics including Simulated Annealing (SA), Genetic Algorithm (GA) and a hybrid of both. The preliminary results indicate that the hybrid method had better performance to achieve the optimal or close to optimal solution.

The efficient evaluation of technological innovation capabilities of enterprises is an important factor to enhance competitiveness. This paper aims to assess and to rank technological innovation evaluation criteria in order to provide a practical insight of systematic analysis by gathering the qualified experts’ opinions combined with three methods of multi-criteria decision making approach. A framework is proposed and uses a novel hybrid multiple criteria decision-making (MCDM) model to address the dependence relationships of criteria with the aid of the Decision-Making Trial and Evaluation Laboratory (DEMATEL), analytical network process (ANP) and VIKOR (VlseKriterijumska Optimizacija I Kompromisno Resenje). The study reports that the interaction between criteria is essential and influences technological innovation capabilities; furthermore, this ranking development of technological innovation capabilities assessment is also one of key management tools for managements of other related high- tech enterprises. Managers can then judge the need to improve and determine which criteria provide the most effective direction towards improvement.

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.