In reality, the machines may interrupt because of the nature of deterioration of the machines. Thus, it is inevitable to perform maintenance alongside production planning. The preventive maintenance is a schedule of strategic operations that are performed prior to the failure occurring, to retain the system operating at the preferred level of consistency. Thus, preventive maintenance plays a significant role in flow shop scheduling models. With its practical significance, this study addresses a practical three-machine n jobs flow shop-scheduling problem (FSSP) in which machine specific preventive maintenance, where each machine is given with a maintenance schedule is considered. In addition, a practical ordered precedence constraint in which some set of jobs has to process in the specified order irrespective of their processing times is also considered. The problem’s goal is to establish the optimal job sequence and preventive maintenance such that the overall cost of tardiness and preventive maintenance is as minimum as possible. An efficient heuristic approach is designed to tackle the present model, resulting in total cost savings. A comparative analysis is not conducted due to absence of studies on the current problem in the literature. However, Computational experiments are carried out on some test instances and results are reported. The reported results may be useful for future studies.

The purpose of this paper is to explore and integrate the role of human resources with the internal practices of the Indian manufacturing industries towards successful implementation of lean manu-facturing (LM). An extensive literature survey is carried out. An attempt is made to build an ex-haustive list of all the input manifests related to human resources and internal practices necessary for LM implementation, coupled with a similar exhaustive list of the benefits accrued from its suc-cessful implementation. A structural model is thus conceptualized, which is empirically validated based on the data from the Indian manufacturing sector. Hardly any survey based empirical study in India has been found to integrate human resources with the internal processes towards success-ful LM implementation. This empirical research is thus carried out in the Indian manufacturing in-dustries. The analysis reveals six key input constructs and three output constructs, indicating that these constructs should act in unison to maximize the benefits of implementing lean. The structural model presented in this paper may be treated as a guide to integrate human resources with internal practices to successfully implement lean, leading to an optimum utilization of resources. This work is one of the very first researches to have a survey-based empirical analysis of the role of human resources and internal practices of the Indian manufacturing sector towards an effective lean im-plementation.

Decision makers of various disciplines are facing challenges because of vast availability of options in the real world. Even though each and every decision made by a decision maker is being done with a great knowledge and conscience, the decision maker needs suitable support to choose the most favorable option to acquire great results in an agile environment. Supplier selection is imperative for an efficient supply chain management. Many industries are in need of effective decision making tools which aids them in valuable supplier selection. This paper proposes a model using Multi Criteria Decision Making (MCDM) tools viz., Grey Relational Analysis (GRA), Analytical Hierarchy Process (AHP) and Technique for Order Performance by Similarity to Ideal Solution (TOPSIS). GRA is used to shortlist the criteria from the available options, while AHP is used to assign weights to the criteria. The final supplier in the selection process is obtained using TOPSIS. The proposed GRA-AHP-TOPSIS model (GRAHP TOP) is used to analyze and formulate the important criteria and the applicability of the model is tested on a case of a small scale industry located in South India.

Quality decisions are one of the major decisions in inventory management. It affects customer’s demand, loyalty and customer satisfaction and also inventory costs. Every manufacturing process is inherent to have some chance causes of variation which may lead to some defectives in the lot. So, in order to cater the customers with faultless products, an inspection process is inevitable, which may also be prone to errors. Thus for an operations manager, maintaining the quality of the lot and the screening process becomes a challenging task, when his objective is to determine the optimal order quantity for the inventory system. Besides these operational tasks, the goal is also to increase the customer base which eventually leads to higher profits. So, as a promotional tool, trade credit is being offered by both the retailer and supplier to their respective customers to encourage more frequent and higher volume purchases. Thus taking into account of these facts, a strategic production model is formulated here to study the combined effects of imperfect quality items, faulty inspection process, rework process, sales return under two level trade credit. The present study is a general framework for many articles and classical EPQ model. An analytical method is employed which jointly optimizes the retailer’s credit period and order quantity, so as to maximize the expected total profit per unit time. To study the behavior and application of the model, a numerical example has been cited and a comprehensive sensitivity analysis has been performed. The model can be widely applicable in manufacturing industries like textile, footwear, plastics, electronics, furniture etc.

The aim of this paper is to apply the technique for order preference by similarity to ideal solution (TOPSIS) as a multi-criteria decision making tool to form the all-time best World XI Test cricket team while taking into consideration over 2600 cricketers participated in Test matches for more than 100 years of cricket history. From the voluminous database containing the performance of numerous Test cricketers, separate lists are first prepared for different positions in the batting and bowling orders consisting of manageable numbers of candidate alternatives while imposing some constraints with respect to the minimum number of innings played (for batsmen), minimum number of tests played (for wicketkeepers and bowlers), and minimum numbers of runs scored and wickets taken (for all-rounders). The TOPSIS method is later adopted to rank those shortlisted cricketers and identify the best performers for inclusion in the proposed World XI Test team. The best World Test cricket team is thus formed as Alastair Cook (ENG) (c), Sunil Gavaskar (IND), Rahul Dravid (IND) (vc), Sachin Tendulkar (IND), Shivnarine Chanderpaul (WI), Jacques Kallis (SA), Adam Gilchrist (AUS) (wk), Glenn McGrath (AUS), Courtney Walsh (WI), Muttiah Muralitharan (SL) and Shane Warne (AUS).

The uncertainty in the supply chains (SCs) for manufacturing and services firms is going to be, over the coming decades, more important for the companies that are called to compete in a new globalized economy. Risky situations for manufacturing are considered in trying to individuate the optimal positioning of the order penetration point (OPP). It aims at defining the best level of information of the client’s order going back through the several supply chain (SC) phases, i.e. engineering, procurement, production and distribution. This work aims at defining a system dynamics model to assess competitiveness coming from the positioning of the order in different SC locations. A Taguchi analysis has been implemented to create a decision map for identifying possible strategic decisions under different scenarios and with alternatives for order location in the SC levels. Centralized and decentralized strategies for SC integration are discussed. In the model proposed, the location of OPP is influenced by the demand variation, production time, stock-outs and stock amount. Results of this research are as follows: (i) customer-oriented strategies are preferable under high volatility of demand, (ii) production-focused strategies are suggested when the probability of stock-outs is high, (iii) no specific location is preferable if a centralized control architecture is implemented, (iv) centralization requires cooperation among partners to achieve the SC optimum point, (v) the producer must not prefer the OPP location at the Retailer level when the general strategy is focused on a decentralized approach.

A dynamic system differs from a static system in that it contains signal factor and the target value depends on the level of the signal factor set by the system operator. The aim of optimizing a multi-response dynamic system is to find a setting combination of input controllable factors that would result in optimum values of all response variables at all signal levels. The most commonly used performance metric for optimizing a multi-response dynamic system is the composite desirability function (CDF). The advantage of using CDF is that it is a simple unit less measure and it has a good foundation in statistical practice. However, the problem with the CDF is that it does not consider the variability of the individual response variables. Moreover, if the specification limits for the response variables are not provided the CDF cannot be computed. In this paper, a new performance metric for multi-response dynamic system, called multiple regression-based weighted signal-to-noise ratio (MRWSN) is proposed, which overcome the limitations of CDF. Two sets of experimental data on multi-response dynamic systems, taken from literature, are analysed using both CDF-based and the proposed MRWSN-based approaches for optimization. The results show that the MRWSN-based approach also results in substantially better optimization performance than the CDF-based approach.

The cooperation in the supply chain assumes an adequate job for enhancing an organisation's performance and increasing competitive advantage. Supply Chain Integration (SCI) affects organisational performance. This paper studies the impact of the integration of supply chain procedures and practices on organisational performance and explores the effect of SCI on organisational performance at Micro, Small and Medium Enterprises (MSMEs) in Madurai District, Tamilnadu, India. A questionnaire is developed with validated measurement scales from previous studies and empirical data are collected through a survey questionnaire from 250 randomly selected MSMEs. This research provides sound recommendations to MSMEs in Madurai District, Tamilnadu, India, and maybe used for different industries and decision making policies. Finally, the study will contribute to the scientific field by providing some future studies.

The main objective of facility location problem is the utilization of the facility by maximum number of possible customers so that the profit is maximized. For instance, in some services like wireless sensor networks, Wi-Fi, repeaters, etc., where the service area is limited, some specific equipment is installed in such a way that it could be used by maximum number of users. Here, the number of users for a particular facility is optimized with the help of clustering technique. The study develops a model for facility allocation problem. For the solution algorithm, a hybrid approach which is based on clustering and mixed integer linear programming (MILP) is proposed. The proposed method consists of two parts where in the first part, the K-means clustering technique is used and in the second part, for each cluster an MILP technique is implemented so that the facility which yields the maximum profit is obtained. Numerical examples for clustering and without clustering are presented. Analysis shows that due to clustering the average distance between facility and customer is significantly reduced.

The aim of this study is to recognize and scrutinize the barriers affecting the utilization of quality tools and techniques (QT&T) in manufacturing organizations. For this purpose, twelve barriers af-fecting the execution of QT&T in manufacturing organizations have been identified from literature analysis and experts’ opinion (academicians and industrial). Questionnaire-based survey has been utilized for the validation of identified barriers. Afterwards, an integrated model of QT&T has been developed by using interpretive structural Modelling (ISM) and Matriced Impacts Croisés Multi-plication Appliquée á un Classement (MICMAC) approach. This research gives an apparent depic-tion to identify and handle the barriers by computing the effectiveness of each barrier. Barriers like accessibility of time and space, inability to change organizational culture and inadequate coordina-tion and teamwork are found to be the key barriers for utilization of QT&T in manufacturing organ-ization. The developed model will help the manufacturing organizations effectively utilize QT&T.