DR. Vinod G. Surange

Associate Professor

PhD, M.E. Mechanical Engineering with specialization in Manufacturing Systems Engineering, B.E. (Mechanical)

Research Interests & Expertise

Operations and Supply Chain Management, Quality Management, Decision science, Supply Chain Risk Management

RESEARCH PAPERS

2023

Modeling Interactions Among Critical Risk Factors in the Indian Manufacturing Industries Using ISM and DEMATEL

Authors: Vinod G. Surange, Sanjay U. Bokade.
Journal: Journal of The Institution of Engineers (India): Series C.
Publication date: 01 Feb 2023
Publisher: Springer
URL: Access Paper

Abstract

This research aims to identify critical risk factors (CRFs) in the various echelons of Indian manufacturing industries and model their interrelationship. This article extracts thirteen CRFs faced by the Indian automotive manufacturing supply chain through a literature review and industry experts’ viewpoints from leading automotive multi-national companies. The interpretive structural modeling method is adopted to model the CRF’s interaction, followed by a matrix of cross-impact multiplications applied to classification analysis for risk classification. The relative importance of each risk factor is computed using the rank-sum weight method. Moreover, the cause-and-effect relationship is visualized in digraph by adopting the Decision-Making Trial and Evaluation Laboratory method. Investigation reveals “Natural disaster,” “ICT Risks,” “Financial Risks,” and “Supplier Risks” as extremely influential CRFs, while “Competitive Risks” and “Delay Risks” appeared to have a high dependency. These results will serve as a vital input in formulating proactive risk mitigation tactics.

Ranking of Critical Risk Factors in the Indian Automotive Supply Chain Using TOPSIS with Entropy Weighted Criterions

Authors: Vinod G. Surange, Sanjay U. Bokade.
Journal: Lecture Notes in Mechanical Engineering
Publication date: 29 April 2023
Publisher: Springer Science and Business Media Deutschland GmbH
URL: Access Paper

Abstract

To survive and grow in today’s world characterized by fierce competition and surrounded by uncertain environments, manufacturing industries are forced to manage internal and external supply chain (SC) disruptions to achieve operational excellence. Automotive manufacturing industries have multiple collaborations at various operations levels, making a complex network of linked activities. Any unprecedented event of slight to severe magnitude adversely hampers various workday activities in the organization. Multiple researchers have cited the susceptibility of the automotive supply chain to numerous risks. Mitigation of risks is vital as complete elimination is impossible on many occasions. This research aims to find out risk factors through a literature review coupled with input from industry experts. After identifying risks, this article ranks the risk factors critical to the automotive SC based on the severity of adverse impacts by considering five different criterions using Technique for Ordered Preference and Similarity to Ideal Solution (TOPSIS). The weight of the evaluation criteria was calculated based on the entropy method. This study identifies thirteen critical risk factors (CRFs), and ranking tools prioritizes “Delay risks,” “Management risks,”, “Supplier risks,” “Employees risks,” and “Inappropriate tools and techniques risks” as the top five CRFs. These research findings will support managers and policymakers framing risk mitigation plans to achieve operational excellence in the entire SC and use the systematic modeling approach to identify CRFs with adverse impacts.

2022

Criticality prioritisation of risk factors in the Indian manufacturing industries using TOPSIS

Authors: Vinod G. Surange, Sanjay U. Bokade.
Journal: International Journal of Business Continuity and Risk Management
Publication date: 31 Aug 2022
Publisher: Inderscience Publishers
URL: Access Paper

Abstract

This article aims to identify the critical risk factors (CRFs) in the Indian manufacturing sector and prioritise them based on their severity. The article further provides the roadmap for effective risk management. Findings from the articles published in peer-reviewed international journals, coupled with the actual industrial scenario, are presented in this paper. This article applies the technique for order preference by similarity to the ideal solution (TOPSIS), one of the key multi-criteria decision-making (MCDM) techniques. Primary data was obtained by consulting fourteen industry experts (IEs) from reputed industries. CRFs are ranked in the order of their criticality based on the input received. This article presents TOPSIS demonstration using R software. The article uncovers the ten CRFs in the manufacturing sector. The ranking tool, with consideration of six selected criteria, derived ‘supplier-related risks’ and ‘design-related risks’, as the foremost risk factors, whereas ‘scope change risk’ and ‘safety-related risk’, obtained a lesser rank.

Implementation of Lean Manufacturing Strategy in Label Printing Industry Using Value Stream Mapping

Authors: Vinod G. Surange, Manas Bhushan Patil, Shivagond Nagappa Teli, Umesh Bhushi.
Journal: 2022 Advances in Science and Engineering Technology International Conferences (ASET)
Publication date: 24 Feb 2022
Publisher: Institute of Electrical and Electronics Engineers Inc.
URL: Access Paper

Abstract

Value-stream mapping is a lean manufacturing tool for analyzing steps performed in an organization or department, of the current state and then designing an ideal form which can be useful for lean strategies within an organization. Value Stream Mapping begins right from the start where the order of product or service is received till it is delivered to the customer through all the manufacturing process steps; these all actions are mapped down physically in a chart. Its main objective is to identify and eliminate all non-value-added activities (waste). Mapping down all the steps followed in production and doing time and motion study helps us know the exact state and find out the places where we are going wrong and improve them by either reducing the wastage or eliminating it. In this paper, we have completed a case study of a label printing industry and recorded information for the same and identified non-value-added activities like waiting time, wastage of labels, etc. and suggested ways to overcome it. By implementing the ideas suggested, it decreased the lead time of the industry, reduced wastage of labels, thereby increasing company efficiency.

Identification and Ranking of Supply Chain Risks Using Fuzzy Topics: A Case Study of Indian Automotive Manufacturing

Authors: Vinod G. Surange, Sanjay U. Bokade.
Journal: Lecture Notes in Mechanical Engineering
Publication date: 23 March 2022
Publisher: Springer Science and Business Media Deutschland GmbH
URL: Access Paper

Abstract

To remain competitive and profit margin in the dynamic market scenario, automotive manufacturing industries are bound to render high-quality products at the optimum cost. However, complexities associated with various interlinked activities in the Automotive Supply Chain (SC) ultimately make the external and internal SC environment extremely uncertain. Firms surrounded by an uncertain environment are exposed to multiple risk factors at all SC echelons causing disruptions that leads to inferior operational performance. Indian automotive industry is a leading industrial sector and set to see immense growth, making a more extensive supply chain network and posing challenges due to increasing complexities. In addition, the level of collaboration and highly complex SC makes the automotive SC vulnerable to risks. The proper assessment of risk factors critical to the automotive SC is essential for policy-makers to build proactive risk mitigation strategies. This study investigates Critical Risk Factors (CRFs) existing in the manufacturing SC of Indian automotive industries. Ranking of identified CRFs is done using the Fuzzy Technique for Order Preference by Similarity to Ideal Solution (FTOPSIS) based on the severity of adverse impact on five criterion using survey data. The results indicate that among the identified 13 CRFs, ‘Delay risks’, ‘Risks related to management’ and ‘Risks related to raw materials’ are crucial to Indian automotive industries. This study’s outcome is expected to assist forefront managers of the Indian automotive sector in framing proactive risk mitigation strategies and adopting a systematic approach for risk prioritization.

2021

Integrated entropy- VIKOR approach for ranking risks in indian automotive manufacturing industries

Authors: Vinod G. Surange, Sanjay U. Bokade, Abhishek Kumar Singh
Journal: Materials Today: Proceedings
Publication date: 21 Nov 2021
Publisher: Elsevier Ltd
URL: Access Paper

Abstract

In today’s VUCA – Volatile, Uncertain, Complex and Ambiguous environment, identifying and prioritizing risks critical to the entire supply chain of automotive manufacturing is imperative. Despite data availability, managers and decision-makers often face trouble while prioritizing risks under varying circumstances due to a lack of a structured approach. This research identifies risks faced by Indian automotive manufacturing industries through literature review and confirms after consulting industry experts. Further, this paper proposes an integrated approach of entropy weighted criteria and VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) for ranking identified critical risk factors in the Indian automotive manufacturing industries. Adverse impact severity of thirteen identified risks on five different criteria “economic aspects”, “factory operations”, “company reputation”, “scheduling” and “quality of the end product/process” and considered during formulation decision matrix. Inputs from seven experts of leading Indian automotive industries were obtained for the overall ranking process. Among identified risks, “Delay Risks”, “Management Risks”, and “Supplier Risks” are ranked as the top three risks faced by Indian automotive manufacturing industries. The structured multi-criteria decision making (MCDM) approach for risks prioritization will guide managers and decision-makers while chalking out risk mitigation plans.

Prioritization of roadblocks to adoption of industry 4.0 technologies in manufacturing industries using VIKOR

Authors: Vinod G. Surange, Sanjay U. Bokade, Abhishek Kumar Singh, S. N. Teli.
Journal: Materials Today: Proceedings
Publication date: 18 Sept 2021
Publisher: Elsevier Ltd
URL: Access Paper

Abstract

To experience seamless adoption of future industry 4.0, it is imperative to investigate its existing roadblocks and success factors in the Indian manufacturing context. Striking similarities among diverse researches highlight the importance of the cyber-physical system assuring many benefits to the manufacturing sector. Many studies concluded that sooner or later, all manufacturing companies will evolve by penetrating industry 4.0 technologies in their enterprise activities. There is a possibility of negative consequences on business functions if top management remains unprepared to assess roadblocks to these future technologies’ adoption. Identification of roadblocks is the first and foremost thing industrial policymakers should focus on. This research enlists the stumbling blocks for industry 4.0 technologies’ adoption that manufacturing industries may encounter by reviewing the latest literature and ranks them using VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) methodology by consulting five experienced Indian industrial authorities. Weightage to each industrial experts’ input is decided by the entropy method. Results indicate that “Skilled workers scarcity,” “Internal employee resistance,” “Worries about cyber security,” and “Inadequate knowledge of/from exterior agencies” are the top four barriers to the incorporation of industry 4.0 technologies in the Indian manufacturing context while “Lack of knowledge about enabling technology solutions” secured lower position. The robustness of the output was checked by carrying out a sensitivity analysis with varying weights. The approach adopted in this study will be helpful for industrial authorities to concentrate their efforts in tackling the most critical barriers. This research will aid industrial decision-makers in remaining proactive during the industrial technology adoption transition.

2015

Implementation of Six Sigma to Reduce Cost of Quality: A Case Study of Automobile Sector

Authors: Vinod G. Surange.
Journal: Implementation of Six Sigma to Reduce Cost of Quality: A Case Study of Automobile Sector
Publication date: 07 Feb 2015
Publisher: Springer Science and Business Media, LLC
URL: Access Paper

Abstract

In the era of cut-throat competition, especially in automobile sector, success of an organization resides in its ability to respond quickly to the needs of its customers. These customer needs must be attended with minimum manufacturing costs, minimum lead time to launch the product in market, and delivering better performance than the existing competitors in the market. Six Sigma is a powerful methodology which ultimately helps in cost reduction. Because of defect prevention and improved product and processes, it leads to increase in profitability and market share. This is accomplished through the use of two Six Sigma sub-methodologies: DMAIC and DMADV (Andersson et al., TQM Mag 18:282–296, 2006). By adopting Design For Six Sigma methodology in the design stage itself leads to launch of a product with maximum quality performance, with tighter tolerances, and with reduced or no defects. This paper considers cost of poor quality as the loss imparted to society from the time the product is shipped, and deals with the applications and benefits of Six Sigma methodology and its positive impact on cost of poor quality. A case study is presented, which enabled application of six sigma methodology in wider range of manufacturing activities. This paper is of value to the researcher in the field of quality management, as well as professionals in the manufacturing industry, wherever the quality improvement is an issue. Quality costs or Cost of Quality is a means to quantify the total cost of quality-related efforts and deficiencies (Banuelas and Antony, TQM Mag 14:92, 2002). The “cost of quality” is not the price of creating a quality product or service. It is the cost of NOT creating a quality product or service. Quality Costs represent the difference between the actual cost of a product or service and what the reduced cost would be if there was no possibility of substandard service, failure of products, or defects in their manufacture.

2014

Impact of poor quality cost in automobile industry

Authors: Vinod G. Surange, S. N. Teli, V. S. Majali, Umesh M. Bhushi.
Journal: International Journal of Quality Engineering and Technology
Publication date: 17 March 2014
Publisher: Inderscience Publishers
URL: Access Paper

Abstract

The present techno-economic scenario is marked by increasing competition in almost every sector of economy, strategy, quality, productivity, profitability and competitiveness. To maximise the profits of an organisation, expectations of customers are on the rise and manufactures have to design and produce goods in as much variety as possible to cater to the demands of the customers. Thus, there is a challenge for industries to manufacture goods of the right quality and quantity, at the right time and at minimum cost for their survival and growth. The cost of poor quality would help in analysing the operating costs for effective and profitable business management. This paper examines the market-oriented aspects of the cost of quality using data from the Indian automotive industry, graphical analysis of impact of quality cost, study of the relationship between unit cost and economies of scale, experience curve effects, and imputed cost of quality in a specific context.

2013

Cost of Poor Quality Analysis for Automobile Industry: A Case Study

Authors: Vinod G. Surange, S. N. Teli, V. S. Majali, U. M. Bhushi, L. M. Gaikwad.
Journal: Journal of The Institution of Engineers (India): Series C.
Publication date: 29 Nov 2013
Publisher: Springer India
URL: Access Paper

Abstract

The high competitiveness makes the quest for production cost reduction a constant in the market, but it is necessary to reduce costs without compromising quality. When a product is in the manufacturing and this has to be scraped, we have more cost than the raw material used, it is necessary to consider the manpower and operations, thus to calculate the cost added to the product. Continuous quality improvement is a key factor in the strategy for competitiveness. Quality cost is one tool, among many others, that can help in continuous quality improvement. Properly applying quality cost techniques is critical to these efforts. Initially, a complete quality cost study could provide awareness and guidance to a steering committee on what cross-discipline teams and improvement projects should be started. The cross discipline teams also can use quality cost special studies to help in focusing efforts. In this paper cost of poor quality analysis has been done using different techniques which are currently applying in automobile industry to assess quality cost.

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Symbiosis International (Deemed University), Nagpur Campus Gat. No.167,168,169, Village Mauje, Bhandewadi, Wathoda Layout, Nagpur, Maharashtra 440008

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0712-6192400 / 0712-6192403

Email Id

admissions@sibmnagpur.edu.in

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