Ritesh Kumar Singh

Bio: Ritesh Kumar Singh is an academic researcher from Birla Institute of Technology, Mesra. The author has contributed to research in topics: Lean manufacturing & Decision support system. The author has an hindex of 11, co-authored 24 publications receiving 796 citations. Previous affiliations of Ritesh Kumar Singh include Birla Institute of Technology and Science.

Implementing the Lean Sigma framework in an Indian SME: a case study

Abstract: Lean and Six Sigma are two widely acknowledged business process improvement strategies available to organisations today for achieving dramatic results in cost, quality and time by focusing on process performance. Lately, Lean and Six Sigma practitioners are integrating the two strategies into a more powerful and effective hybrid, addressing many of the weaknesses and retaining most of the strengths of each strategy. Lean Sigma combines the variability reduction tools and techniques from Six Sigma with the waste and non-value added elimination tools and techniques from Lean Manufacturing, to generate savings to the bottom-line of an organisation. This paper proposes a Lean Sigma framework to reduce the defect occurring in the final product (automobile accessories) manufactured by a die-casting process. The proposed framework integrates Lean tools (current state map, 5S System, and Total Productive Maintenance (TPM)) within Six Sigma DMAIC methodology to enhance the bottom-line results and win customer loyalty. Implementation of the proposed framework shows dramatic improvement in the key metrics (defect per unit (DPU), process capability index, mean and standard deviation of casting density, yield, and overall equipment effectiveness (OEE)) and a substantial financial savings is generated by the organisation.

Lean tool selection in a die casting unit: a fuzzy-based decision support heuristic

Abstract: Lean manufacturing philosophy asks for elimination of wastes hidden in the manufacturing system by focusing on product value stream and eliminating non-value adding activities through continuous improvement efforts. Value stream mapping methodology is subjected to principles of continuous improvement in order to improve the productivity of the process and quality of the product. It provides various tools for data collection and analysis, and identifies the wastes occurring in different stages of manufacturing process. The role of value stream mapping is very important in the identification and subsequently reduction of the wastes. To select the detailed mapping tools for the identification of waste at micro level is a complex decision making problem. In this paper, a case study related to a die casting unit has been taken. A hierarchy related to the decision problem has been developed to select the value stream mapping tools. Here, a fuzzy logic based multi-preference, multi-criteria, and multi-person dec...

Justification for the selection of a reconfigurable manufacturing system: a fuzzy analytical hierarchy based approach

Abstract: The aim of this article is to highlight a novel production system paradigm entitled the Reconfigurable Manufacturing System (RMS) and study its pre-design strategies. Here a decision-making module is established for the evaluation of existing and new generation manufacturing systems by trading off among the tangible and intangible design parameters. This difficult and time-consuming process is carried out using the Analytical Hierarchy Process (AHP), a widely used process to solve multi-criteria decision-making problems. In order to capture the vagueness and uncertainty of the decision-makers’ judgment, fuzzy logic is introduced into the pairwise comparison of alternatives. In order to provide the designers with a systematic framework to evaluate different alternatives to support their manufacturing system choice, in this paper a model has been proposed to quantify those features of MSs that aid in rapidly adjusting their capability to production functionality (convertibility). After providing the mathema...

Toyota production system : beyond large-scale production

Abstract: * Starting from Need* Evolution of the Toyota Production System* Further Development* Genealogy of the Toyota Production System* The True Intention of the Ford System* Surviving the Low-Growth Period

Review: A state-of the-art survey of TOPSIS applications

Abstract: Multi-Criteria Decision Aid (MCDA) or Multi-Criteria Decision Making (MCDM) methods have received much attention from researchers and practitioners in evaluating, assessing and ranking alternatives across diverse industries. Among numerous MCDA/MCDM methods developed to solve real-world decision problems, the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) continues to work satisfactorily across different application areas. In this paper, we conduct a state-of-the-art literature survey to taxonomize the research on TOPSIS applications and methodologies. The classification scheme for this review contains 266 scholarly papers from 103 journals since the year 2000, separated into nine application areas: (1) Supply Chain Management and Logistics, (2) Design, Engineering and Manufacturing Systems, (3) Business and Marketing Management, (4) Health, Safety and Environment Management, (5) Human Resources Management, (6) Energy Management, (7) Chemical Engineering, (8) Water Resources Management and (9) Other topics. Scholarly papers in the TOPSIS discipline are further interpreted based on (1) publication year, (2) publication journal, (3) authors' nationality and (4) other methods combined or compared with TOPSIS. We end our review paper with recommendations for future research in TOPSIS decision-making that is both forward-looking and practically oriented. This paper provides useful insights into the TOPSIS method and suggests a framework for future attempts in this area for academic researchers and practitioners.

Fuzzy multiple criteria decision-making techniques and applications - Two decades review from 1994 to 2014

Abstract: Two decades was systematically reviewed on fuzzy MCDM techniques from 1994 to 2014.The database for review was 403 papers from more than 150 high-ranking journals.403 scholarly papers were grouped in four different main fields.Papers were classified based on utilizing, developing and proposing research papers. MCDM is considered as a complex decision-making tool involving both quantitative and qualitative factors. In recent years, several fuzzy FMCDM tools have been suggested to choosing the optimal probably options. The purpose of this paper is to review systematically the applications and methodologies of the fuzzy multi decision-making (FMCDM) techniques. This study reviewed a total of 403 papers published from 1994 to 2014 in more than 150 peer reviewed journals (extracted from online databases such as ScienceDirect, Springer, Emerald, Wiley, ProQuest, and Taylor & Francis). According to experts' opinions, these papers were grouped into four main fields: engineering, management and business, science, and technology. Furthermore, these papers were categorized based on authors, publication date, country of origin, methods, tools, and type of research (FMCDM utilizing research, FMCDM developing research, and FMCDM proposing research). The results of this study indicated that, in 2013, scholars have published papers more than other years. In addition, hybrid fuzzy MCDM in the integrated method and fuzzy AHP in the individual section were ranked as the first and second methods in use. Additionally, Taiwan was ranked as the first country that contributed to this survey, and engineering was ranked as the first field that has applied fuzzy DM tools and techniques.

Lean manufacturing: literature review and research issues

Abstract: Purpose – The advent of recession at the beginning of twenty-first century forced many organizations worldwide to reduce cost and to be more responsive to customer demands. Lean Manufacturing (LM) has been widely perceived by industry as an answer to these requirements because LM reduces waste without additional requirements of resources. This led to a spurt in LM research across the globe mostly through empirical and exploratory studies which resulted in a plethora of LM definitions with divergent scopes, objectives, performance indicators, tools/techniques/methodologies, and concepts/elements. The purpose of this paper is to review LM literature and report these divergent definitions, scopes, objectives, and tools/techniques/methodologies. Design/methodology/approach – This paper highlights various definitions by various researchers and practitioners. A total of 209 research papers have been reviewed for the research contribution, research methodology adopted, tools/techniques/methodologies used, type of industry, author profile, country of research, and year of publication. Findings – There are plethora of LM definitions with divergent objectives and scope. Theory verification through empirical and exploratory studies has been the focus of research in LM. Automotive industry has been the focus of LM research but LM has also been adopted by other types of industries also. One of the critical implementation factors of LM is simultaneous adoption of leanness in supply chain. LM has become an integrated system composed of highly integrated elements and a wide variety of management practices. There is lack of standard LM implementation process/framework. Originality/value – The paper reviews 209 research papers for their research contribution, research methodology, author profile, type of industry, and tools/techniques/methodology used. Various characteristics of LM definitions are also reviewed.