Operations Research, Systems Engineering and Industrial Engineering Commons^™

A Transdisciplinary Collaboration And Innovation Education Model And Experience, Brian Laduca, Michelle Hayford, Adrienne Ausdenmoore, Jerome Yorke, Kevin Hallinan, Rebecca Blust, Anne R. Crecelius, Philip Appiah-Kubi, Jennifer Katz-Buonconintro, Jana Bennett, Jackie Marshall Arnold, Connie L. Bowman, Castel Sweet

Engineering Management and Systems Faculty Publications

As the interconnectedness of the world grows, the need to prepare college students capable of addressing complexity likewise grows. In this context, the University of Dayton has developed and tested a transdisciplinary model for education. This model links multiple classes from different disciplines via a common theme and within a common space. It also employs an educational model premised on the following trajectory: disciplinary content development / transdisciplinary observation (empathy); transdisciplinary disruption leading to “A-Ha” observations which transform the disciplinary directions; and lastly transdisciplinary informed design and research. Central to this model is a 3,500 square foot common space used …

The Business Case For Industrial Safety: Revealing The Comprehensive Value Of Ergonomic Investments For Manufacturing Enterprises In Industry 4.0, Shane Stan

Honors Theses

How can today’s manufacturing enterprises construct, implement, and optimize modern safety initiatives in a manner that will present maximum return on investment and facilitate enterprise growth? Furthermore, how can these manufacturers assure individual ergonomic investments become part of a larger strategy to facilitate organizational change in safety? This work addresses these questions by placing industrial ergonomics in a business improvement context which comprehensively presents the financial returns and growth opportunities poised by modern safety initiatives. Additionally, to further strengthen the business case for industrial safety, an ergonomic action planning framework is established to guide the creation of holistic safety programs …

Data-Driven Predictive Maintenance Scheduling Policies For Railways, Pedro Cesar Lopes Gerum, Ayca Altay, Melike Baykal-Gürsoy

Supply Chain Management

Inspection and maintenance activities are essential to preserving safety and cost-effectiveness in railways. However, the stochastic nature of railway defect occurrence is usually ignored in literature; instead, defect stochasticity is considered independently of maintenance scheduling. This study presents a new approach to predict rail and geometry defects that relies on easy-to-obtain data and integrates prediction with inspection and maintenance scheduling activities. In the proposed approach, a novel use of risk-averse and hybrid prediction methodology controls the underestimation of defects. Then, a discounted Markov decision process model utilizes these predictions to determine optimal inspection and maintenance scheduling policies. Furthermore, in the …

Paints-R-Us Term Project, Tyler Campbell, Skye Gilbreth, Michael Oluwole, Elijah Raffo, Brad Unruh

Engineering and Technology Management Student Projects

This project will consider a linear product mix optimization problem for a fictional paint company, Paints-R-Us. Paints-R-Us is a wholesale paint manufacturer located in the Pacific Northwest. The Global Production Manager, Steve Brush, has been tasked with maximizing Paints-R-Us’s profit in the upcoming quarter. Steve Brush oversees the global production plan, and in collaboration with the production planners will develop a production plan which optimizes the profits that Paints-R-Us can create in the quarter accounting for the following criteria:

• Demand in the given quarter for each of the 5 paint types that Paints-R-Us produces • The warehousing storage capacity …

Correlation-Sensitive Next-Basket Recommendation, Duc Trong Le, Hady Wirawan Lauw, Yuan Fang

Research Collection School Of Computing and Information Systems

Items adopted by a user over time are indicative ofthe underlying preferences. We are concerned withlearning such preferences from observed sequencesof adoptions for recommendation. As multipleitems are commonly adopted concurrently, e.g., abasket of grocery items or a sitting of media consumption, we deal with a sequence of baskets asinput, and seek to recommend the next basket. Intuitively, a basket tends to contain groups of relateditems that support particular needs. Instead of recommending items independently for the next basket, we hypothesize that incorporating informationon pairwise correlations among items would help toarrive at more coherent basket recommendations.Towards this objective, we develop a …

Coordinating Supply And Demand On An On-Demand Service Platform With Impatient Customers, Jiaru Bai, Kut C. So, Christopher S. Tang, Xiqun Chen, Hai Wang

Research Collection School Of Computing and Information Systems

We consider an on-demand service platform using earning sensitive independent providers with heterogeneous reservation price (for work participation) to serve its time and price sensitive customers with heterogeneous valuation of the service. As such, both the supply and demand are "endogenously'' dependent on the price the platform charges its customers and the wage the platform pays its independent providers. We present an analytical model with endogenous supply (number of participating agents) and endogenous demand (customer request rate) to study this on-demand service platform. To coordinate endogenous demand with endogenous supply, we include the steady-state waiting time performance based on a …

Natural Resources Governance Employing Blockchain-Based Decision-Making, Farinaz Sabz Ali Pour, Adrian Gheorghe

Engineering Management & Systems Engineering Faculty Publications

Natural resources are essential structures of socio-economic systems which shape the well-being of humanity, environment, and the economy. Human actions have become the critical responsibility for environmental changes and pressuring many planetary boundaries. Having a systematic approach can provide a governance platform including the inherent characteristics of the resource, the historically established form of use, and transaction costs. A natural resource governance framework is developed by applying Blockchain technology as the primary goal of this study to regulate and manage the extraction and trades. Blockchain technology provides a distributed concurrency monitoring system for sustainable resource management. Persistent and pervasive cooperation …