A Gamification Approach for Experiential Education of Inventory Control

In this educational research project, game-based in-class and after-class learning activities are developed to teach selected inventory control strategies to undergraduate and graduate students. Students from Supply Chain Management and System Simulation courses are targeted, who are taught by different instructors. The activities include teaching the inventory control policies to students in a regular class setting, then providing an overview on a game developed on MS Excel. In the game, the lead time and customer demand variables are defined uncertain, and not given to students, which make the assignment an ill-structured problem. A 12-month planning and execution period is given to students with qualitative and quantitative information about 3 products. The students are given a 1-week period to play the game. The game simulates selected inventory control strategies with reorder point and order quantity parameters for 12 months. The learning outcomes of the course related to inventory control, and students’ experience with the game are surveyed. Survey results are statistically and visually analyzed. Overall results indicated that the proposed gamification approach is found to have positive impact in learning effectiveness in the majority of evaluation categories. In addition, the contribution of the proposed gamification approach was found to be effectively supporting the learning outcomes of the course

TRACI Impact Assessment of Transportation Manufacturing Nexus in the U.S.: A Supply Chain-Linked Cradle-to-Gate LCA

Sustainable transportation is an inevitable component of sustainable development intitiatives for mitigating the climate change impacts and stabilizing the rising carbon emissions thus global temperature. In this context, comprehensive analysis of the environmental impact of transportation can play a critical role towards quantifying the midpoint environmental and human health related impacts associated with the transportation activities triggered by manufacturing sectors. This study traces the life cycle impact of the U.S. transportation and manufacturing sectors’ nexus using Tool for the Reduction and Assessment of Chemicals and Other Environmental Impacts (TRACI) in the context of the Economic Input-Output Life Cycle Assessment (EIO-LCA) framework considering the following midpoint impact categories: ‘global warming’, ‘particulate matter’, ‘eutrophication’, ‘acidification’, and ‘smog air’. Both direct (onsite) and indirect (supply chain) industries’ relationships with transportation industry are considered as the main scope. Results indicated that top ten contributor manufacturing sectors accounted for over 55% total environmental impacts on each impact category. Additionally, based on the decomposition analysis, food manufacturing sector was found to be the major contributor to smog air with an approximate share of 21% in the entire supply chain. Automobile related manufacturing sectors also have significant impact on all five life cycle impact categories that the environmental impact of transportation is higher than on-site (direct) impact. Overall decomposition analysis of 53 manufacturing sector indicated that the environmental impact of transportation has severe effects on ‘smog air’, ‘eutrophication’ and ‘acidification’ with a share of 16.4%, 10.5%, and 6.0%, respectively. When we consider the average percentage share of transportation related environmental impact on the entire supply chain, U.S manufacturing sectors have a negative impact with a share of 18.8% of ‘smog air’, 16.8% for ‘eutrophication’, and 8.1% for ‘acidification’

Life Cycle Assessment and Optimization-Based Decision Analysis of Construction Waste Recycling for a LEED-Certified University Building

The current waste management literature lacks a comprehensive LCA of the recycling of construction materials that considers both process and supply chain-related impacts as a whole. Furthermore, an optimization-based decision support framework has not been also addressed in any work, which provides a quantifiable understanding about the potential savings and implications associated with recycling of construction materials from a life cycle perspective. The aim of this research is to present a multi-criteria optimization model, which is developed to propose economically-sound and environmentally-benign construction waste management strategies for a LEED-certified university building. First, an economic input-output-based hybrid life cycle assessment model is built to quantify the total environmental impacts of various waste management options: recycling, conventional landfilling and incineration. After quantifying the net environmental pressures associated with these waste treatment alternatives, a compromise programming model is utilized to determine the optimal recycling strategy considering environmental and economic impacts, simultaneously. The analysis results show that recycling of ferrous and non-ferrous metals significantly contributed to reductions in the total carbon footprint of waste management. On the other hand, recycling of asphalt and concrete increased the overall carbon footprint due to high fuel consumption and emissions during the crushing process. Based on the multi-criteria optimization results, 100% recycling of ferrous and non-ferrous metals, cardboard, plastic and glass is suggested to maximize the environmental and economic savings, simultaneously. We believe that the results of this research will facilitate better decision making in treating construction and debris waste for LEED-certified green buildings by combining the results of environmental LCA with multi-objective optimization modeling

Multi-Period Cell Loading and Job Sequencing in a Cellular Manufacturing System

In this paper, a multi-period cell loading problem is addressed, where the objectives are to minimise the number of tardy jobs (nT) in a multi-period planning horizon and optimise the scheduling of tardy jobs. Three cell loading and job scheduling strategies are proposed and tested with two newly developed mixed integer programming models. Additionally, three types of due dates (tight, medium and loose) and three different demand levels were considered. Finally, two tardy job assignment methods were proposed to observe the impact on nT. Case problems were solved based on minimising nT, Tmax and total tardiness (TT) objectives and cost sensitivity analysis was performed. Results indicated that, the first strategy, (early start allowance and tardy job assignment after each period) performed better in terms of nT. For the secondary objectives, tradeoffs were observed among different strategies depending on the type of due date, demand level and tardy job assignment method

The Cost-of-Living Index for OECD Countries Pre and Post Covid-19 Pandemic

This research was done to look and see how the cost-of-living index was affected during the pandemic. We took data on thirty-seven different countries that are members of the Organization for Economic Co-operation and Development (OECD), to ensure we could get as much data on these counties as possible. The cost-of-living index is a compilation of things that affect individuals\u27 budgets on the daily. This includes childcare costs, healthcare costs, food and nonalcoholic beverages, housing costs, and transportation. By using a Mann-Whitney U test to compare each variable\u27s pre pandemic (2017-2019) data to the post pandemic (2020-2021) data we were able to see if the cost of living increased during the pandemic, and if so, did average wages increase as well. We chose to research this because it is a problem that we all deal with daily, and we thought it would provide practical knowledge for everyone

Life Cycle Assessment and Optimization-Based Decision Analysis of Construction Waste Recycling for a LEED-Certified University Building

The current waste management literature lacks a comprehensive LCA of the recycling of construction materials that considers both process and supply chain-related impacts as a whole. Furthermore, an optimization-based decision support framework has not been also addressed in any work, which provides a quantifiable understanding about the potential savings and implications associated with recycling of construction materials from a life cycle perspective. The aim of this research is to present a multi-criteria optimization model, which is developed to propose economically-sound and environmentally-benign construction waste management strategies for a LEED-certified university building. First, an economic input-output-based hybrid life cycle assessment model is built to quantify the total environmental impacts of various waste management options: recycling, conventional landfilling and incineration. After quantifying the net environmental pressures associated with these waste treatment alternatives, a compromise programming model is utilized to determine the optimal recycling strategy considering environmental and economic impacts, simultaneously. The analysis results show that recycling of ferrous and non-ferrous metals significantly contributed to reductions in the total carbon footprint of waste management. On the other hand, recycling of asphalt and concrete increased the overall carbon footprint due to high fuel consumption and emissions during the crushing process. Based on the multi-criteria optimization results, 100% recycling of ferrous and non-ferrous metals, cardboard, plastic and glass is suggested to maximize the environmental and economic savings, simultaneously. We believe that the results of this research will facilitate better decision making in treating construction and debris waste for LEED-certified green buildings by combining the results of environmental LCA with multi-objective optimization modeling

Socio-Eco-Efficiency Analysis of Highways: A Data Envelopment Analysis

To ensure the large network of highways is performing sustainably, there is a dire need to quantify sustainability for highways. In this paper, data envelopment analysis (DEA) based mathematical model is developed to evaluate sustainability in an attempt to aid these efforts. Sustainability goals pertaining to the three dimensions of sustainability, social, economic and environmental, were utilized. Utilizing the developed model, sustainability scores of thirty highway sections were calculated and ranked accordingly. Percent improvement analysis was carried out to gain more insight. In addition, sensitivity analysis was carried out to understand how different values of input parameters impacted the socio-eco-efficiency of each highway section. The aim of the study was to show that DEA based sustainability assessment model could be used to evaluate highways and assist in strategic planning goals of transportation agencies. Results indicated that 22% to 47% reductions are required to be achieved on negative social and environmental impacts for the inefficiency highway sections to be 100% efficient while keeping the economic indicators the same

Multi-region Input-Output-based Carbon and Energy Footprint Analysis of U.S. Manufacturing

In this research, U.S. manufacturing activities' life cycle-based carbon and energy footprint impacts have been quantified, taking international trade linkages with the rest of the world into account. The U.S economy has been integrated into a multi-region input-output (MRIO) life cycle assessment framework where total of 40 major economies, including the USA, China, Russia, and others, plus the rest of the world (ROW) were modelled to assess global energy and carbon footprint impacts. Each country's economy is assumed to compromise 35 major industries based on the WIOD database classification. A total of 1435 (41 × 35 = 1435) industries has therefore been taken to represent the global structure of the world economy. The novelty of the approach is that the MRIO model has been developed in a stochastic fashion, plus global trade-linked uncertainties have also been taken into consideration. Top carbon emitting and energy consumer industries and countries have been analysed using data analytics and statistical modelling methods. The results show that the USA is the largest contributor to the total carbon footprint (CFP) and the total energy footprint (EFP) with 81.73% and 84%, respectively. Moreover, the agriculture/hunting forestry/fishing sector and the electricity/gas/water supply sectors dominate the overall U.S. carbon footprint, contributing 22% and 21.28%, respectively. The coke/refined petroleum/nuclear fuel sector has the largest share of the total energy footprint, with 47.9% of the total impacts

A Project-based Learning Approach in Teaching Simulation to Undergraduate and Graduate Students

In this study, application of experiential learning into graduate and undergraduate curricula of a industrial system simulation course is presented. Simulation has been among the courses against which students feel uncomfortable or frightened due to heavy software use, prerequisite of probability, and statistics knowledge, and its application requirements. To minimize this fear and improve student’s understanding about the subject matters and have them develop ample skills to build complex models, a project-based learning approach is proposed and used in undergraduate and graduate teaching settings. To achieve the project-based learning goals, a 15-week curriculum is designed to have a balanced lecture and lab sessions, which are specifically designed to address the needs of the term project as the semester continues. In the term project, groups of 2-3 students were asked to form a group, where each group was expected to work on a real system to 1) understand, conceptualize, and model the existing system as a mental, then software-model; 2) validate the existing system model statistically; 3) identify areas for improvement (in addition to the ones given by the supervisor); 4) complete the project with testing out system improvement scenarios and conducting cost/benefit analysis. The effectiveness of project-based learning is surveyed and studied based on the course learning outcomes. The results indicated that the proposed project-based learning approach was found to be effective in students’ learning experience and critically supportive on reaching the learning outcomes, and it was found that students’ learning and skills of simulation modeling and application are improved regardless of their grade

Assessing an Online Engineering Ethics Module from Experiential Learning Perspective

Today, engineers play a crucial role in the direction of technology, research, social wellbeing, and economic growth, thus the lives of people. An engineer’s professional responsibility for complying with ethical standards and conduct is essential to the needs and requirements of individuals, organizations, and the society. Educating the future engineering workforce and establishing effective and timely policies that ensure engineering professional’s compliance with requirements are two important pillars of sustaining the ethical knowledge and practice in engineering profession. In this study, the researchers focused on investigating the learning effectiveness of an online ethics module developed for and implemented in a senior year Engineering Ethics Seminar course. The module consisted of three pillars: code of ethics, case studies, and methods for applying ethical reasoning. Each pillar requires the student to take a quiz consisting of 4 to 7 questions, and a final 10 question quiz at completion of the module. In-class activities and assignments complement the module. The research team conducted a two-semester assessment on learning effectiveness of the online ethics module with a sample of 41 engineering students from well-represented diverse majors, self-identification and racial/ethnic backgrounds compared to the enrollment population. Results indicate that the proposed online module positively impacted the students’ proficiency in knowledge of ethics and ethical reasoning in terms of students’ perception of improved confidence and the instructor’s assessment. The same interpretation was reached by the instructor’s assessment as well. The team did not identify any correlation between the students’ answers to the survey questions and their final grades, which indicates that the students’ positive response on their learning experience was found to be independent of their letter grade