4 Presentations

• 
  01:30 PM - 01:55 PM

  How to set the deadline and the penalty policy for a new environmental standard

  • Amirmohsen Golmohammadi, presenter, Laurentian University
  • Tim Kraft, North Carolina State Univesity

  Air pollution is a growing environmental challenge for both developing and developed countries. In this study, we explore how governments can use environmental standards to combat firms’ air pollution. We focus on two penalty policies, per-period and per-unit penalty policies, and examine how a government should set the deadline and the penalty for a standard in a market with two competing firms, both of whom make technology development decisions. We analyze and compare the government’s decisions under both penalty policies. Our results show that only when one of the firms has a significantly higher development capability and/or production capability should the government set the deadline in a way such that only one firm complies on time. When we compare the two penalty policies, we find that the per-unit penalty policy typically results in a later or equal deadline and a higher or equal penalty as compared to the per-period penalty policy.
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  01:55 PM - 02:20 PM

  A Risk Assessment Approach for Blockchain Technology Adoption in Sustainable Supply Chains

  • Samuel Yousefi, presenter, University of British Columbia - Okanagan
  • Babak Mohamadpour Tosarkani, University of British Columbia - Okanagan

  The inherent features of blockchain technology (BT) increase the capability of continuous tracking of products and make supply chains more responsive to socio-environmental concerns. Although BT is known as an innovative tool, there are some potential risks (e.g., adoption cost and operation complexity) affecting BT adoption. This study proposes a decision support system to help managers analyze the risks associated with BT adoption and identify critical ones to minimize their adverse effects during the adoption process in sustainable supply chains. The decision support system is developed based on the extended version of the data-driven cognitive map in the Z-number environment to model the causal relationships between the economic, social, and environmental-related risks. In addition to causal relationships, this system also considers uncertainty and reliability concepts in determining the values of risk factors to calculate the criticality degree of each risk. These criticality degrees are calculated using the hybrid learning algorithm embedded in the proposed system. The outputs of this study imply that the adoption cost, extra audits, regulatory uncertainty, and energy consumption are the most critical risks associated with BT adoption.

  Keywords: Sustainable supply chain; Blockchain technology; Risk assessment; Decision support system.
• 
  02:20 PM - 02:45 PM

  A Slope Scaling Heuristic for the Multiperiod Strategic Planning of Carbon Capture and Sequestration

  • Gabriel Homsi, presenter, Université de Montréal
  • Étienne Ayotte-Sauvé, CanmetENERGY
  • Sanjay Dominik Jena, Université du Québec à Montréal

  To meet the objectives of the Paris Agreement, global efforts are currently underway to implement various decarbonization strategies in all sectors of economic activity. One such strategy is carbon capture and storage (CCS), which involves capturing CO2 at emitter sites, and transporting it to geological sequestration sites, where it is to be injected underground for long-term storage. In this work, we focus on the multiperiod strategic planning of a CCS supply chain involving pipeline CO2 transportation. From an operations research standpoint, such a problem exhibits the characteristics of combined facility location and network design. 

  To account for multiple sources of data uncertainty, this problem may be solved thousands of times. Thus, reaching high-quality solutions quickly is paramount. 

  As commercial solvers struggle to provide high-quality solutions under these time constraints, we propose a slope scaling heuristic based on previous work for single period CCS and network design. This heuristic approximates the cost of design variables, generates upper bounds with dynamic programming, has long-term memory strategies, and has a final improving phase where a restricted model is solved. 

  Computational experiments show that the proposed heuristic generates better solutions than CPLEX for most instances considered, at a fraction of the time. 
• 
  02:45 PM - 03:10 PM

  The perspective of X-Reality in disassembly 4.0 for End-of-Life product management

  • Yinong Yang, presenter, Polytechnique Montreal
  • Samira Keivanpour, Polytechnique Montréal

  In the context of sustainable and smart manufacturing, the applications of advanced technologies in End-of-Life (EoL) product management are evolving. Industry 4.0 has led to the ongoing integration of digital technologies into traditional (re)manufacturing. Disassembly plays an essential role in product recovery and EoL strategies. However, the current disassembly operations are still manual and labor-intensive. Few studies have examined how digital technology affects the decision-making and management of disassembly processes. Among all Industry 4.0 technologies, X-Reality (XR) has been adopted to be an integrative visualizing and monitoring assistant in some service-oriented applications. XR refers to its constituting technologies spanning Augmented Reality (AR), Virtual Reality (VR), and Mixed Reality (MR). Despite its widespread use, XR’s benefits for disassembly remain under investigated. This study synthesizes the existing literature on how XR can enhance disassembly and identifies the key opportunities in Disassembly 4.0.