Srikanta Routroy

Bio: Srikanta Routroy is an academic researcher from Birla Institute of Technology and Science. The author has contributed to research in topics: Supply chain & Supply chain management. The author has an hindex of 16, co-authored 100 publications receiving 1028 citations.

Comparing the performance of neural networks developed by using Levenberg-Marquardt and Quasi-Newton with the gradient descent algorithm for modelling a multiple response grinding process

Abstract: Highlights? Levenberg-Marquardt (L-M) and Boyden, Fletcher, Goldfarb and Shanno (BFGS) update Quasi-Newton (Q-N)-based BPNN networks are equally efficient as adaptive learning (A-L) algorithm-based BPNN network. ? L-M algorithm has fastest network convergence rate, followed by BFGS update Q-N and A-L algorithm. ? A-L -based BPNN learns faster than BFGS update Q-N, and L-M takes maximum time for network training. ? A-L algorithm is relatively easy-to-understand and implement, as compared to L-M or BFGS update Q-N algorithm, for online process control. Monitoring and control of multiple process quality characteristics (responses) in grinding plays a critical role in precision parts manufacturing industries. Precise and accurate mathematical modelling of multiple response process behaviour holds the key for a better quality product with minimum variability in the process. Artificial neural network (ANN)-based nonlinear grinding process model using backpropagation weight adjustment algorithm (BPNN) is used extensively by researchers and practitioners. However, suitability and systematic approach to implement Levenberg-Marquardt (L-M) and Boyden, Fletcher, Goldfarb and Shanno (BFGS) update Quasi-Newton (Q-N) algorithm for modelling and control of grinding process is seldom explored. This paper provides L-M and BFGS algorithm-based BPNN models for grinding process, and verified their effectiveness by using a real life industrial situation. Based on the real life data, the performance of L-M and BFGS update Q-N are compared with an adaptive learning (A-L) and gradient descent algorithm-based BPNN model. The results clearly indicate that L-M and BFGS-based networks converge faster and can predict the nonlinear behaviour of multiple response grinding process with same level of accuracy as A-L based network.

Agriculture supply chain: A systematic review of literature and implications for future research

Abstract: The purpose of this paper is to review the agriculture supply chain (ASC) literature along many dimensions which include but are not restricted to scope, objective, wastages, driver, obstacle, outcome, etc,In total, 203 relevant and scholarly articles of various researchers and practitioners during 2000-2016 were reviewed The information related to definition, research methodology, global research spread, supply chain strategy, various types of produce, author profile and year of publication of ASC were collected and analysed,The information related to empirical research and viewpoint of various ASC drivers were captured, studied and analysed in detail Although inventory policy, demand forecasting and ASC integration were found to be important areas of ASC, they were less focused, studied and researched,Mainly post-harvest ASC of different agricultural produces were considered whereas products such as dairy, fishery and meat supply chains were not included in the study,The paper provides an insight into various aspects of ASC in general and one can get a deeper and richer knowledge on it which will help in formulating effective strategies to design of an effective and efficient ASC It uncovers the research gaps for the new future research paths This systemic review is strongly felt to fill the gap in the ASC literature

Evaluating the critical success factors of supplier development: a case study

Abstract: Purpose – The purpose of this paper is to identify and evaluate the critical success factors (CSFs) responsible for supplier development (SD) in a manufacturing supply chain environment.Design/methodology/approach – In total, 13 CSFs for SD are identified (i.e. long‐term strategic goal; top management commitment; incentives; supplier's supplier condition; proximity to manufacturing base; supplier certification; innovation capability; information sharing; environmental readiness; external environment; project completion experience; supplier status and direct involvement) through extensive literature review and discussion held with managers/engineers in different Indian manufacturing companies. A fuzzy analytic hierarchy process (FAHP) is proposed and developed to evaluate the degree of impact of each CSF on SD.Findings – The degree of impact for each CSF on SD is established for an Indian company. The results are discussed in detail with managerial implications. The long‐term strategic goal is found to be ...

State-of-the-art literature review on inventory models for perishable products

Abstract: The purpose of this paper is to review and analyze the perishable inventory models along various dimensions such as its evolution, scope, demand, shelf life, replenishment policy, modeling techniques and research gaps.,In total, 418 relevant and scholarly articles of various researchers and practitioners during 1990-2016 were reviewed. They were critically analyzed along author profile, nature of perishability, research contributions of different countries, publication along time, research methodologies adopted, etc. to draw fruitful conclusions. The future research for perishable inventory modeling was also discussed and suggested.,There are plethora of perishable inventory studies with divergent objectives and scope. Besides demand and perishable rate in perishable inventory models, other factors such as price discount, allow shortage or not, inflation, time value of money and so on were found to be combined to make it more realistic. The modeling of inventory systems with two or more perishable items is limited. The multi-echelon inventory with centralized decision and information sharing is acquiring lot of importance because of supply chain integration in the competitive market.,Only peer-reviewed journals and conference papers were analyzed, whereas the manuals, reports, white papers and blood-related articles were excluded. Clustering of literature revealed that future studies should focus on stochastic modeling.,Stress had been laid to identify future research gaps that will help in developing realistic models. The present work will form a guideline to choose the appropriate methodology(s) and mathematical technique(s) in different situations with perishable inventory.,The current review analyzed 419 research papers available in the literature on perishable inventory modeling to summarize its current status and identify its potential future directions. Also the future research gaps were uncovered. This systemic review is strongly felt to fill the gap in the perishable inventory literature and help in formulating effective strategies to design of an effective and efficient inventory management system for perishable items.

Modeling information risk in supply chain using Bayesian networks

Abstract: Purpose – Information sharing enhances the supply chain profitability significantly, but it may result in adverse impacts also (e.g. leakages of secret information to competitors, sharing of wrong information that result into losses). So, it is important to understand the various risk factors that lead to distortion in information sharing and results in negative consequences. Information risk identification and assessment in supply chain would help in choosing right mitigation strategies. The purpose of this paper is to identify various information risks that could impact a supply chain, and develop a conceptual framework to quantify them. Design/methodology/approach – Bayesian belief network (BBN) modeling will be used to provide a framework for information risk analysis in a supply chain. Bayesian methodology provides the reasoning in causal relationship among various risk factors and incorporates both objective and subjective data. Findings – This paper presents a causal relationship among various info...

Defining Lean Production : Some conceptual and practical issues

Abstract: Purpose - This paper aims to investigate the definition of Lean Production and the methods and goals associated with the concept as well as how it differs from other popular management concepts. Methodology/Approach - The paper is based on a review of the contemporary literature on Lean Production, both journal articles and books. Findings - It is shown in the paper that there is no consensus on a definition of Lean Production between the examined authors. The authors also seem to have different opinions on which characteristics that should be associated with the concept. Overall it can be concluded that Lean Production is not clearly defined in the reviewed literature. This divergence can cause some confusion on a theoretical level, but is probably more problematic on a practical level when organizations aim to implement the concept. This paper argues that it is important for an organization to acknowledge the different variations, and to raise the awareness of the input in the implementation process. It is further argued that the organization should not accept any random variant of Lean, but make active choices and adapt the concept to suit the organization-s needs. Through this process of adaptation, the organization will be able to increase the odds of performing a predictable and successful implementation. Originality/Value - This paper provides a critical perspective on the discourse surrounding Lean Production, and gives an input to the discussion of the implementation of management models. Keywords - Lean Production, Definition, Construct Validity, Total Quality Management Paper type - Conceptual paper

DEMATEL Technique: A Systematic Review of the State-of-the-Art Literature on Methodologies and Applications

Abstract: Decision making trial and evaluation laboratory (DEMATEL) is considered as an effective method for the identification of cause-effect chain components of a complex system. It deals with evaluating interdependent relationships among factors and finding the critical ones through a visual structural model. Over the recent decade, a large number of studies have been done on the application of DEMATEL and many different variants have been put forward in the literature. The objective of this study is to review systematically the methodologies and applications of the DEMATEL technique. We reviewed a total of 346 papers published from 2006 to 2016 in the international journals. According to the approaches used, these publications are grouped into five categories: classical DEMATEL, fuzzy DEMATEL, grey DEMATEL, analytical network process- (ANP-) DEMATEL, and other DEMATEL. All papers with respect to each category are summarized and analyzed, pointing out their implementing procedures, real applications, and crucial findings. This systematic and comprehensive review holds valuable insights for researchers and practitioners into using the DEMATEL in terms of indicating current research trends and potential directions for further research.