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Evangelista, PhD FOREWORD Paul Evangelista Copyright (c) 2021-04-09 2021-04-09 9 1 1 1 10.37266/ISER.2021v9i1.pp1 Modeling and Analysis in Support of Organizational Decisions During the COVID-19 Pandemic The 2019 coronavirus disease (COVID-19) disrupted economic and social systems on an unprecedented scale. Organizational leaders faced unstructured problems that required novel analysis and evidenced-based decision-making approaches. This paper explains several analytical tools and problem-solving methodologies used at the United States Military Academy at West Point to support decision-making related to operational activities and future planning. While many of the tools apply basic analytical methods, the novelty of this paper lies in the unique application of the tools, visual presentation of data analytics, and the explanation of the contextual circumstances that prompted the development of these tools. Paul Evangelista Nicholas Clark Matthew Dabkowski Ian Kloo Copyright (c) 2021 Industrial and Systems Engineering Review 2021-04-09 2021-04-09 9 1 2 14 10.37266/ISER.2021v9i1.pp2-14 Analyzing the Manufacturing Supply Chain Performance for Urgent Item During COVID-19 Outbreak As COVID-19 pandemic spreads in different regions with varying intensity, supply chains (SC) need to utilize an effective mechanism to adjust spike in both supply and demand of resources, and need techniques to detect unexpected behavior in SC at an early stage. During COVID-19 pandemic, the demand of medical supplies and essential products increases unexpectedly while the availability of recourses and raw materials decreases significantly. As such, the questions of SC and society survivability were raised. Responding to this urgent demand quickly and predicting how it will vary as the pandemic progresses is a key modeling question. In this research, we take the initiative in addressing the impact of COVID-19 disruption on manufacturing SC performance overwhelmed by the unprecedented demands of urgent items by developing a digital twin model for the manufacturing SC. In this model, we combine system dynamic simulation and artificial intelligence to dynamically monitor SC performance and predict SC reaction patterns. The simulation modeling is used to study the disruption propagation in the manufacturing SC and the efficiency of the recovery policy. Then based on this model, we develop artificial neural network models to learn from disruptions and make an online prediction of potential risks. The developed digital twin model is aimed to operate in real-time for early identification of disruptions and the respective SC reaction patterns to increase SC visibility and resilience. Ali Arishi Krishna K Krishnan Vatsal Maru Copyright (c) 2021 Industrial and Systems Engineering Review 2021-04-09 2021-04-09 9 1 15 31 10.37266/ISER.2021v9i1.pp15-31 Production Planning and Emergency Inventory for Demand Surge in Health Supply Chains for Pandemics like COVID-19 This research considers modeling production and inventory quantities in the presence of demand surge due to pandemics like Covid-19. The aim of this research is to help health care organizations better prepare and respond to a demand surge due to a pandemic. A large-scale pandemic such as Covd-19 can cause an overwhelming demand for urgent medical supplies in a very short notice. Well-established supply chain planning and modeling are necessary to avoid any national level or company health supply chain problems resulting from demand shortages. This paper addresses the issues from supply chain perspective. The need to be prepared for any surge in demand is addressed in terms of emergency inventories, including those of Work-in-Process and finished goods. Linear Programming models are developed to minimize the costs of production, inventories, and transportation of goods from one stage to next stage. Several scenarios are tested out for various levels of demand, cost, and capacities. Amro Khaswaneh Nagen Nagarur Copyright (c) 2021 Industrial and Systems Engineering Review 2021-04-09 2021-04-09 9 1 32 46 10.37266/ISER.2021v9i1.pp32-46 Workplace Assigned Mobile Communication Devices and Employee Stress A literature review of the important role played by stress in workplace performance, the correlation between workplace assigned mobile communication devices and stress as well as measures that can be taken to alleviate such stress is presented in this paper. Workplace stress can cause problems ranging from mild anxiety to serious problems which could cause death. Stress can also have an adverse effect on the productivity and morale of employees. The modern workplace is rife with a large variety of stressors. With the rapid advance in communications technology, mobile communication devices are new possible stressors which have become widely prevalent over the past few years. These devices allow employees to be in constant communication with workplace activities. They are invaluable tools for employees who travel frequently and who are required to be on call. This paper seeks to present a review of current literature that investigates the possible correlation between workplace stress and mobile communication devices. Managers that require employees to monitor their communication device after work hours and while on vacation could be placing undue stress on their employees’ well-being. Some employees feel that they will miss out on something or get into trouble if they are not in constant communication. A separation between work and personal life must be present to reduce stress among employees and managers. Such a separation is vital to the health and well being of all concerned. The role played by workplace assigned mobile communication devices has been studied in this paper. This is a timely addition to the literature in this area in light of the increasingly ‘mobile’ nature of the modern workplace. Anoop A Desai Michael Ball Copyright (c) 2021 Industrial and Systems Engineering Review 2021-04-09 2021-04-09 9 1 47 55 10.37266/ISER.2021v9i1.pp47-55 Safety and Health Implications of COVID-19 on the United States Construction Industry The construction industry is an essential U.S. business sector, yet it suffers from an elevated risk for work-related fatalities and injuries. The COVID-19 pandemic has only exacerbated this risk, as well as shone a light on the severe economic/financial/labor burdens and safety/health concerns the sector has faced. As such, the purpose of this review paper is to synthesize the safety and health issues associated with COVID-19 pandemic in the construction industry, and summarize the challenges and opportunities for construction stakeholders in implementing COVID-19 safety and health measures in the construction industry. This paper has explored the challenges in construction and COVID-19; COVID-19 knowledge, preventative behaviors, and risk perception among construction workers; recommendations/practical implications/preventive measures; and COVID-19 education in compliance/guidance, strategies to combat impacts of COVID-19 pandemic, smart digital technologies, and worker wellbeing and work-related quality of life (e.g., mental health). It is warranted that the construction industry needs to take better steps in preparing for future, man-made or natural disaster events, and subsequent acute and chronic disease risk, in order to yield a healthier/safer construction workplace. Sang D Choi John Staley Copyright (c) 2021 Industrial and Systems Engineering Review 2021-04-09 2021-04-09 9 1 56 67 10.37266/ISER.2021v9i1.pp56-67 A Mathematical Model for In-Person Office Assignment During COVID-19 The global pandemic that is COVID-19 has altered our world as we know it. Educational systems have been seriously affected, businesses – whether “essential” or not – have been severely stressed, how people socialize has, perhaps forever, been changed, and telecommuting is the new norm. The purpose of this paper is to discuss a situation wherein a company was having difficulty in scheduling their in-person office staffing in a move to allow rotational schedules for their employees to decongest their office when an entirely telecommuting operation was not possible. Due to the different types of employees, their various work-related constraints, and the need to minimize the number of bodies in the office while addressing minimum coverage necessary to perform the company’s daily activities, a quick solution to their scheduling/assignment needs was not obvious or trivially obtained. As such, mathematical models, specifically, integer programming assignment models, were developed and ultimately solved using the Python/Gurobi solver to address their scheduling needs. This paper will describe the constraints faced by the company and the models developed to solve their tricky assignment problem. Daryl Santos Copyright (c) 2021 Industrial and Systems Engineering Review 2021-04-09 2021-04-09 9 1 68 74 10.37266/ISER.2021v9i1.pp68-74