Operations Research By S D Sharma Pdf
Rubie Mccloughan
Neha Sharma is an Assistant Professor of Operations, Information and Decisions at The Wharton School, University of Pennsylvania. Her research focuses on design of online marketplaces using data, stochastic models, and game theory.
This course introduces basic concepts of operations management and application of the same in business practice today. We will examine the theoretical foundations of operations management and how these principles or models can be employed in both tactical and strategic decision making. Topics covered in detail are forecasting techniques, planning under deterministic and uncertain demand, operations planning and scheduling, queuing theory, service operations management, newsvendor models, risk pooling strategies in firms, capacity and revenue management, and supply chain coordination. We will conclude by discussing how supply chains evolve under technological change.
Dr. Jitendra Sharma is Professor of Operations Management and teaches an elective course in Quality Management Systems along with Six Sigma. His research involves using QFD to address quality and customer centric issues in product development. He also teaches Operations Management and Lean Systems. He has more than 40 international peer reviewed journal publications to his credit.
Professor Sharma has also authored numerous cases on the topics of operations and process management, including topics such as inventory management, MRP, AHP, forecasting, process planning and control, process and capacity management, six sigma, SQC, target costing, value analysis, sales and operations planning, etc. These cases are hosted with Harvard Business Publishing, Ivey Cases, Emerald and The Case Centre. Some of his best selling cases have been translated in Spanish and Chinese.
Professor Sharma does lean, six sigma, process and operations management training for executives of companies like Asian Paints. He holds a Ph.D. in Mechanical Engineering from the NIT, Raipur He also holds an M.Tech. from Nagpur University, MBA in Operations from IGNOU and a B. Engineering in Production from Nagpur University. Before diving into the world of academics he worked with different manufacturing industries as an engineer. He has a work experience of 30 years, of which 5 years were in industry and remaining in academics.
Nestled in the lap of nature, IMT Nagpur has accomplished much in over two decade. IMT Nagpur is home to some of the finest faculty with troves of knowledge and industry experience. The pedagogy adopted here is action-oriented, developed to meet the requirements of modern business world.
In today's business, environment natural and manmade disasters like recent event (Covid 19) have increased the attention of practitioners and researchers to Supply chain vulnerability. Purpose of this paper is to investigate and prioritize the factors that are responsible for supply chain vulnerability. Extant literature review and interviews with the experts helped to extract 26 supply chain vulnerability factors. Further, the relative criticality of vulnerability factors is assessed by analytical hierarchy process (AHP). Critical part supplier; location of supplier; long supply chain lead times; Fixing process owners and mis-aligned incentives in supply chain are identified as the most critical factors among twenty-six vulnerability factors. Research concludes that not only long and complex supply chain but supply chain practices adopted by firms also increase supply chain vulnerability. Relative assessment of vulnerability factors enables professionals to take appropriate mitigation strategies to make the supply chains more robust. This research adds in building a model for vulnerability factors that are internal to supply chain & controllable.
Literature on supply chain vulnerability (SCV) provides some conceptual frameworks and a very few empirical studies, though literature on supply chain risk management has vast coverage in terms of conceptual frameworks and mathematical models. There is difference in supply chain risk and supply chain vulnerability. Risk is outcome (always negative in case of supply chain disruptions) and vulnerability is a driving force that leads to risk in supply chain (El Baz & Ruel, 2020; Marvin et al., 2020). Research has developed various qualitative and quantitative models for supply chain risk assessment, the present literature lacks in assessing the Supply Chain Vulnerability factors. SCV is precondition to supply chain risks. SCV is the result of various supply chain decisions that increase the exposure of supply chain to various disruptions (Ivanov & Sokolov, 2019). Literature on supply chain resilience have provided discussion on supply chain design and its relationship with resilience. Literature is lacking discussions on supply chain practices that may cause vulnerability. This research aims to develop a supply chain vulnerability model in the context of emerging economies. SCV in form of index, does not provide any help to managers, rather if its formulated into criteria and sub-criteria form, managers have some start points for mitigation. There is a need to study and provide a definitive weightage to each of the criteria and sub-criteria. This would help in identifying the highly critical factors and focused approach to minimize SCV. In the current COVID scenario, it is therefore both critical to first identify the various supply chain factors in manufacturing sector and then, to compute the crisp priority score for each criterion. This rationalizes the formulation of the following two important research questions answered through this research.
In this paper, a supply chain vulnerability hierarchical framework is proposed and developed. The framework embeds the vulnerability factors also known as pressure points in supply chain that may cause disruptions. Certain pressure points in supply chain can have too low pressure or too high pressure, depending on the supply chain resources, management styles and supply chain design parameters. Main aim of this research is to identify comprehensive and relevant supply chain vulnerability factors, wherein firms have control power to adjust the SCV underlying factors known as SCV drivers. Then research aims to utilize analytic hierarchy process for prioritizing identified SCV factors.
The proposed supply chain vulnerability framework is based on expert survey in manufacturing industry and extensive literature review. The next section provides the literature review from supply chain risk and vulnerability perspectives. Section 3 explained research framework used in this research. Section 4 provides detailed view on research methodology to answer the research questions. Then next Sect. 5 describes the use of proposed model through a case application in Indian manufacturing industry. Section 6 provides a discussion on results and then Sect. 7 briefly discusses theoretical and managerial implications of the research. Last Sect. 8 concludes the main findings and future scope of research.
DuHadway et al. (2019) developed a framework for supply chain risk management and concluded that it is important to understand the reasons that generate supply chain risks. Supply chain risks are the events that affect the supply chain goals and causes losses to firms. Supply chain vulnerability is precondition to supply chain risk. SCV exposes supply chain to external or internal risk (Chiu & Choi, 2016; Wagner & Bode, 2006).
Several factors and trends make modern supply chains more vulnerable (Christopher & Lee, 2004; Fawcett & Waller, 2014a). Some trends like outsourcing, globalization, low cost countries sourcing, lean inventories, efficient and more responsive business processes, rationalization of supplier base etc. have resulted in massive pressures on supply chains (Fisher, 1997; Jttner et al., 2003). (Rao & Goldsby, 2009) provided a topology of supply chain risk and identified risks both internal and external to the supply chain. Jain et al. (2017) studied enablers of supply chain resilience and found that assets at strategic locations in supply chain increase resilience. Choudhary et al.(2015) found that network structure has direct impact on supply chain vulnerability. SCV factors or drivers (referred in this research) may be internal or external to supply chain. Internal drivers are supply chain design related and external are environmental (country specific or natural). Following list, captures SCV drivers from literature and some driver might have different number of sub factors. Purpose of this classification is to bring SCV drivers and showing their presence in literature. SCV drivers and their sub drivers are shown in following Table 1.
Is indicated by the number of alternative suppliers that are available for particular component (Hallikas et al., 2005). As number of nodes in upstream or downstream increases the supply chain complexity increases. This increased number of nodes in supply chain causes coordination difficulty and may results into errors in processes. Simultaneously, alternative suppliers reduces the dependencies and reduces the vulnerability in supply chain (Paksoy et al., 2019).
Is represented by number of linkages emerging out and merging in from a particular node. For a particular node if number of linkages coming in are more than number of linkages going out it becomes more vulnerable. The focal company is forced to have substantial losses if there are any disruptions from the customer side. A situation in which buying firms have a limited no. of suppliers is called as Node Concentration. There is an increase in supply chain vulnerability due to the growing reduction of suppliers and having closer contact with less suppliers (T. Y. Choi & Krause, 2006). Supply base reduction has advantages such as increased product quality but the firm lacks contingency suppliers in case of supply disruption. Single sourcing occurs when there is extreme case of supplier concentration (Abdel-Basset & Mohamed, 2020).
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