Dr. Sube Singh
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Academic Career Length
9Years (2018-Present)
(Calculated once Scilit publication data is synced: current year − year of first publication + 1)
Representative Publications
View All Publications29 July 2020 in International Journal of Production Research
Journal Article
Sube SinghRKRamesh Kumar
Ramesh KumarRPRohit Panchal
Rohit PanchalMTManoj Kumar Tiwari
Manoj Kumar TiwariAn outbreak of deadly COVID-19 virus has not only taken the lives of people but also severely crippled the economy. Due to strict lockdown, the manufacturing and logistics activities have been suspended, and it has affected the demand and supply of various products as a result of restrictions imposed on shopkeepers and retailers. Impacts of COVID-19 are observed ubiquitously in every type of units from different sectors. In this study, a simulation model of the public distribution system (PDS) network is developed with three different scenarios to demonstrate disruptions in the food supply chain. Difficulties have been increased in matching supply and demand in a vast network of PDS because of changing scenarios with the growth of infected cases and recovery. This paper also highlights the importance of a resilient supply chain during a pandemic. Our proposed simulation model can help in developing a resilient and responsive food supply chain to match the varying demand, and then further assist in providing decision-making support for rerouting the vehicles as per travel restrictions in areas. Paper has been summarised with significant highlights and including future research scope for developing a more robust food supply chain network.
18 April 2019 in International Journal of Computer Integrated Manufacturing
Journal Article
Sube SinghSGSoumava Ghosh
Soumava Ghosh
JJJayanth Jayaram
Jayanth Jayaram
MTManoj Kumar Tiwari
Manoj Kumar TiwariToday’s scenario of manufacturing and supply chain is full of uncertainty because of numerous types of disruptions and failures such as fire, storm, machine failure, are a few names. Always supply chain disruptions present disastrous impacts, although probabilities of happening are low. In the recent robust as well as flexible supply chain has captured the focus of researchers in designing a supply chain network with consideration of disruption’s risk. In this work, an ontology-based decision support system is proposed to intensify the supply chain resilience during a disruption. The concept of semantic and ontology is adopted in developing the knowledge base for the entire supply chain network including manufacturing units. Protégé is used for defining the classes and sub-classes along with numerous types of properties and expressed in a rule-based system using semantic web rule language (SWRL). Furthermore, a mixed integer linear programming model with an objective of maximising quantified resilience to fulfil the demand. A hybrid particle swarm optimisation – differential evolution (PSO-DE) is utilised as an optimisation technique for the defined problem. In performing the study, a set of simulated data is formed and then interpreted in the ontology for an optimal selection of recovery activity.
25 November 2018 in International Journal of Computer Integrated Manufacturing
Journal Article
The world has seen tremendous changes in manufacturing, since its first industrial revolution to the current era of Industry 4.0. In the past few years, numerous advanced manufacturing models have been introduced by researchers and the same was implemented by companies. Similarly, in this domain, a new concept of inclusive manufacturing (IM) has been coined by Inclusive Manufacturing Forum for inclusive growth of manufacturing sector. In this work, a conceptual model of inclusive manufacturing system (IMS) is proposed along with a framework and flow chart. The IM is a composition of various policies and standards for resolving societal issues, environmental degradation and economic difficulties along with the integration of advanced manufacturing models and emerging technologies, like information and communication technologies, cyber-physical system, Internet of Things and Semantic Web. The vision of the proposed concept is to achieve the target of minimum time to market, high quality, low cost, better service, clean environment, flexible and precise information sharing. In this work, IMS has been conceptualised, along with visualisation of its practical implication by considering numerous emerging and supportive technologies, for achieving the goal of better collaboration among micro, small and medium enterprises.
1 January 2019 in IFAC-PapersOnLine
Journal Article
Sube SinghABAnkit Barde
Ankit Barde
BMBiswajit Mahanty
Biswajit Mahanty
MTM.K. Tiwari
M.K. Tiwari
11 April 2019 in International Journal of Computer Integrated Manufacturing
Journal Article
LMLohithaksha M. Maiyar
Lohithaksha M. Maiyar
Sube SinghVPVittal Prabhu
Vittal Prabhu
MTManoj Kumar Tiwari
Manoj Kumar TiwariMinimising total production time in the additive or layered manufacturing is a critical concern, and in this respect, the idea of balancing assembly time and build time is rapidly gaining research attention. The proposed work intends to provide benefit in terms of reduced lead time to customers in a collaborative environment with simultaneous part printing. This paper formulates a mixed-integer non-linear programming (MINLP) model to evaluate the near optimal threshold area and support material allocation while segregating parts for a single material additive manufacturing set-up. The resulting time minimisation model is finitely bounded with respect to support material volume, total production time and total assembly cost constraints. A novel swarm intelligence-based part segregation procedure is proposed to determine the number of part assemblies and part division scheme that adheres to cross-sectional shape, cross-sectional area, and height restrictions. The proposed approach is illustrated and evaluated for objects with regular as well as free-form surfaces using two different hypothetically simulated real size 3D models. Results indicate that the proposed approach is able to reduce the total amount of manufacturing time in comparison with single part build time for all the tested cases.
10 April 2018 in International Journal of Current Microbiology and Applied Sciences
Journal Article
International Journal of Current Microbiology and Applied Sciences ISSN:2319-7692(Print), ISSN:2319-7706(Online) is a multidisciplinary peer-reviewed journal with reputable academics and experts as members of its Editorial Board. The Current Microbiology aims to publish all the latest and outstanding research articles. Review and letters in all areas of major importance to techniques of microbiology and applied research with publishes high quality of review and research articles on novel aspects of Microbiology including Environmental, Food, Agricultural, Medical, Pharmaceutical, Veterinary, Soil, Water and Biodeterioration.
About Me
Dr. Sube Singh has been an Assistant Professor of Supply Chain at Warwick Manufacturing Group (WMG), University of Warwick, UK, since May 2023. His research focuses on developing tools and methodologies for supply chain management, with emphasis on sustainability, resilience, and digitalisation. He is actively involved in several major projects, including the JLR-WMG Supply Chain Innovation Hub, addressing real-world supply chain challenges for Jaguar Land Rover; the EPSRC-funded Hydrogen Integration for Accelerated Energy Transitions (HI-ACT) programme; and an AI-Driven Digital Twin of Semiconductor Supply Chains (SCDT) project funded by UKIERI-SPARC in collaboration with IIT Kharagpur. He also contributes to the Supply Chain Digitisation Educational Package (SCDEP) funded by Digital Catapult, aimed at industry training. Dr. Singh holds a PhD in Industrial Engineering from IIT Kharagpur. He previously held a postdoctoral position at Clemson University (CU-ICAR), USA, and worked as a Research Assistant at NITIE, Mumbai. His academic background includes a B.Tech. and M.Tech. in Mechanical Engineering from GJUS&T Hisar and MNNIT Allahabad, respectively. He was also a Visiting Research Student at Loughborough University, UK. His research has been published in leading journals such as the International Journal of Production Research and the ASME Journal of Computing and Information Science in Engineering, with over 1,500 citations and an H-index of 6.