Search results

The purpose of this paper is to minimize the mean flow time in open shop scheduling problem (OSSP). The scheduling problems consist of n jobs and m machines, in which each job has O operations. The processing time for 50 OSSP was generated using a linear congruential random number.

Different evolutionary algorithms are used to minimize the mean flow time of OSSP. This research study used simulated annealing (SA), Discrete Firefly Algorithm and a Hybrid Firefly Algorithm with SA. These methods are referred as A1, A2 and A3, respectively.

A comparison of the results obtained from the three methods shows that the Hybrid Firefly Algorithm with SA (A3) gives the best mean flow time for 76 percent instances. Also, it has been observed that as the number of jobs increases, the chances of getting better results also increased. Among the first 25 problems (i.e. job ranging from 3 to 7), A3 gave the best results for 13 instances, i.e., for 52 percent of the first 25 instances. While for the last 25 problems (i.e. Job ranging from 8 to 12), A3 gave the best results for all 25 instances, i.e. for 100 percent of the problems.

From the literature it has been observed that no researchers have attempted to solve OOSPs using Firefly Algorithm (FA). In this research work an attempt has been made to apply the FA and its hybridization to solve OSSP. Also the research work carried out in this paper can also be applied for a real-time Industrial problem.

Sustainable supply chain management (SSCM) concepts have received immense attention in the recent past in both academia and industries. Especially, manufacturing industries in developing countries realize the importance of adopting sustainability concepts in their supply chain. The SSCM adoption has not been to the same level across different manufacturing sectors and hence a single implementation framework will not have the same effect across sectors. This paper aims to compare the adoption level of 25 SSCM practices across three major manufacturing sectors, namely, automobile, electronics and textile, in an emerging economy, India.

A questionnaire-based data collection technique is used to obtain adoption levels of each of the identified SSCM practices on a five-point Likert-type scale with “1” representing not considering presently to “5” indicating successful implementation. Second, a hypothesis is framed and tested to compare the adoption levels across sectors using a one-way single-factor ANOVA followed by a post hoc test by Tukey’s test.

The results derived suggest that though the industries across different sectors are in the course of adopting SSCM practices, the level of adoption is found to be not the same. The textile sector has adopted the least, and the electronic sector edges ahead of the automobile sector in terms of successful transformation to SSCM.

This study focuses on the differences and similarities in the adoption of policies in the automobile, electronics and textile sectors using statistical data analysis tools. A total of 25 individual practices are identified from existing literature and classified into six groups, namely, management, supplier, collaboration, design, internal and society, based on their similarities. Based on a detailed questionnaire survey with industrial experts in relevant fields as respondents, the adoption levels of practices are rated individually and categorically.

Friction welding is a solid state bonding process, where the joint between two metals has been established without melting the metal. The relative motion between the faying surfaces (surfaces to be joined) under the application of pressure promotes surface interaction, friction and heat generation which subsequently results in joint formation. Stainless steel is an iron based alloy, contains various combinations of other elements to give desired characteristics, and found a wider range of applications in the areas such as petro‐chemical, fertilizer, automotive, food processing, cryogenic, nuclear and beverage sectors. In order to exploit the complete advantages of stainless steels, suitable joining techniques are highly demanded. The Friction welding is an easily integrated welding method of stainless steel, which considered as non‐weldable through fusion welding. Grain coarsening, creep failure and failure at heat‐affected zone are the major limitations of fusion welding of similar stainless steels. Friction welding eliminates such pitfalls. In the present work an attempt is made to investigate experimentally, the mechanical and metallurgical properties of friction welded joints, namely, austenitic stainless steel (AISI 304) and ferritic stainless steel (AISI 430). Evaluation of the characteristics of welded similar stainless steel joints are carried out through tensile test, hardness measurement and metallurgical investigations.

The purpose of this paper is to present an approach to identify and rank the criteria used for the supplier development using interpretative structural modeling (ISM).

The paper develops a framework to analyze the interactions among the criteria such as competitive pressure, evaluation and certification system, incentives, supplier development programs, inter‐organizational communication, buyer‐supplier relationship, supplier commitment, supplier performance, asset specificity, joint action, trust, long‐term strategic goals, top management support, purchasing performance, and supplier strategic objective for the supplier development using ISM. The developed framework is illustrated using a case study taken in an automobile firm.

The paper contributes to research in supply chain management (SCM) and particularly in supplier development. Research in the area of SCM has intensified in recent years for a number of reasons. Managers have now realized that actions taken by one member of the chain can influence the responsiveness, efficiency and profitability of the complete supply chain. Firms are increasingly thinking in terms of competing as part of a supply chain against other supply chains, rather than as a single firm against other individual firms.

Since the proposed framework is applied for only a single company, further studies can be done using the same framework for several companies in India. This will provide a better understanding of how the variables that influence supplier development are affected in different types of industry.

Managers can use the proposed framework to develop better relationships with suppliers and to create management responses that influence and improve their relationships with them.

This paper uses 15 criteria to propose a framework for the supplier development and also finds the interactions between the criteria which influence the most and the least to improve the relationship with the suppliers.

The purpose of this study is to optimize the process parameters (wire feed rate (F), voltage (V), welding speed (S) and torch angle (A)) in order to obtain the optimum bead geometry (bead width (W), reinforcement (R) and depth of penetration (P)), considering the ranges of the process parameters using evolutionary algorithms, namely genetic algorithm (GA) and simulated annealing (SA) algorithm.

The modeling of welding parameters in flux cored arc welding process using a set of experimental data and regression analysis, and optimization using GA and SA algorithm.

The adequate mathematical model was developed. The multiple objectives were optimized satisfactorily by the GA and SA algorithms. The feasible solution results are very closer to the optimized results and the percentage error was found to be negligibly small.

The optimal welding parameters were identified in order to increase the productivity. The welding input parameters effect was found.

Connected machines are the automation of several types of machines connected towards beneficial growth of sustainable construction especially in the era of the Fourth Industrial Revolution. This chapter gave an insight into the emergence of digitalisation in the construction sector and the importance of connected machines in sustainable construction. It further elucidated its mode of operations, devices applicable, drivers and challenges for its full application in construction and benefits on construction projects. It finally gave a conclusion on its urgent need for full incorporation due to its technological benefits for present and future construction works.

The purpose of this paper is to optimize the gas metal arc welding (GMAW) process input parameters simultaneously considering the multiple output variables (bead width (BW), bead height (BH) and depth of penetration (DP)).

Grey‐based Taguchi approach was used for designing the experiment, L27 orthogonal array was used which composed of three levels and 27 rows, which means that 27 experiments were carried out. Design of experiments was selected based on a four welding parameters with three levels each. The selected welding parameters for this paper are gas flow rate, voltage, travel speed and wire feed rate. The bead‐on‐plate welding trials are carried out on AISI 904L super austenitic stainless steel (SASS) sheets and evaluate the shape of the fusion zone depends upon a number of input parameters.

Bead‐on‐plate welding of 904L SASS sheet is successfully performed (without any cracks and discontinuity) by GMAW process and the bead profiles are measured. The predicted bead profiles have the better DP and lower BH and BW. It is found that the optimized setting values are improving the response values by 10 per cent.

The optimal welding conditions are identified in order to increase the productivity and minimize the total operating cost. The process input parameters effect is determined under the optimal welding combinations.

The paper addresses supplier selection in the public procurement sector. The motivation is providing a decision-making tool that mimics the intuitive behavior of the public tender committee in evaluating the bid according to predefined (quantitative and qualitative) criteria by a strict and transparent procedure, in accordance with governmental procurement regulations and requirements. To this aim, we address the supplier selection decision problem in the public procurement sector by a well-known fuzzy multiple criteria decision- making approach. Using the presented technique enables evaluation of both imprecise information and quantitative data in vendor selection, while keeping the transparency features requested in public procurement. We show the effectiveness and efficiency of the approach with a case study involving an Italian public administration.

The purpose of this paper is to present a research model that explore strategic outsourcing practices for sustainable competitive advantages. In this paper, a decision support system (DSS) for sustainable performance measurement of carry and forward agents (CFAs) is proposed.

The importance of seven criteria as a means of selecting the best CFA for warehouses under the aspect of sustainable environment is analyzed. The criteria are compared and ranked using analytic hierarchy process (AHP) with the combined assistance of literature review and expert opinions. This study makes use of unstructured interviews of Regional Distribution Manager and senior strategic leaders of the firms.

This paper discusses how strategic outsourcing can help firm to achieve desired business outcomes. The selection of best CFA gives a direction to the company to move toward excellence and provides the key areas to work upon to achieve competitive advantage. The main contribution of this paper includes modeling the performance evaluation problem within the context of a sustainable supply chain based on triple bottom line (TBL) concept.

The identified selection criteria are bound with Indian transportation and logistics industry. Further, it is suggested to conduct a real-life application of this study to other companies from different countries, to obtain criteria based on globally acceptable norms. The results may yield the network-specific evaluation criteria and their evaluations.

The developed excel-based tool could be used to record the inspection data, compare the CFAs and determine the best CFAs on the basis of selected criteria. With the help of this tool, CFAs know their position and ranking among all the CFAs and the focus areas they need to work upon to perform well. The training module could be used to keep the CFA staff on the right track which is very essential in a typical manufacturing industry warehouse. The improved performance of CFAs will in turn help to improve the manufacturing process, thus maximizing the gains along with environmental benefits.

This paper provides a priority of sustainable issues for evaluating the performance of the best CFA. The paper presents a strategic outsourcing model, which suggest both theoretical and managerial implications showing how to implement successful outsourcing practices in the global market by analyzing the performance of outsourcing partners, i.e. CFAs.

The purpose of this paper is to extend an approach to solve linear programming problems with grey data and variables, based on a developed multi‐objective programming approach.

The proposed approach to generally solve the grey linear programming problems is based on the notion of order relation between interval grey numbers. This notion is applied to cascade the grey objective function to a bi‐objective problem based on the objective function of the original problem. The same approach is taken to transform grey constraints to a set of corresponding linear constraints. Finally, the obtained multi‐objective model can be solved by any existing methods in the literature.

One of the shortcomings of previous approaches to solve grey linear programming problems was that they required the grey coefficients of objective function to be both side negative or positive. The approach proposed here does not have such a requirement and guarantees the feasibility of solutions.

A different approach is developed in the paper that can be used to solve grey linear programming problems in general form. The method relaxes the limitation of existing approaches.