Operations Research, Systems Engineering and Industrial Engineering Commons^™

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 …

The Impact Of Executing A Warehouse Management System Change: A Case Study, Nicholas J. Cross

Masters Theses & Specialist Projects

The increased demand on distribution centers to provide quicker turnarounds from receiving to shipping while maintaining precise inventory accuracies is spurring the acquisition of a warehouse management system (WMS) to improve operations and increase efficiency. With the rapid expansion of WMS technology, it seems inevitable that warehouses will outgrow inefficient operational processes and switch to a system that can accommodate rapid development. Research has explained the financial burdens and benefits of acquiring a WMS, but there’s been minimal research describing the impacts of the actual implementation. This study took place within a 600,000 sq. ft. fulfillment center and focused on …

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 …

Backhaul Profit Maximization Problem Instances, Yuanyuan Dong, Yulan Bai, Eli V. Olinick, Andrew Junfang Yu

Operations Research and Engineering Management

This archive contains data for the problem instances described in the technical report "An Empirical Study of Mixed Integer Programming Formulations of the Backhaul Profit Maximization Problem" by Yulan Bai and Eli V. Olinick.

An Empirical Study Of Mixed Integer Programming Formulations Of The Backhaul Profit Maximization Problem, Yulan Bai, Eli V. Olinick

Operations Research and Engineering Management

Solving an instance of the Backhaul Profit Maximization Problem (BPMP) requires simultaneously solving two problems: (1) determining how to route an empty delivery vehicle back from its current location to its depot by a scheduled arrival time, and (2) selecting a profit-maximizing subset of delivery requests between various locations on the route subject to the vehicle's capacity. We propose and test a series of enhancements to the node-arc and triples mixed integer programming formulations of BPMP found in the literature and develop a multi-criteria Composite Index Method (CIM) to evaluate the results. We find that CPLEX takes 5 to 34 …

Modeling The Economic Machine Using Bayesian Inference And Statistical Networks, And Optimal Portfolio Construction Using Operations Research, Richard Yang

ENGS 88 Honors Thesis (AB Students)

In this paper, we propose a network-based model to attempt to connect modern macroeconomic theory with real world economic observations and trends. We find that by extending macroeconomic theory with credit leveraging/deleveraging thresholds, we are able to explain economic cycles in addition to long-term growth. Furthermore, we specifically explore the growth-inflation view of the macro economy as a basis for optimal portfolio construction and efficient asset trading. Connecting our network-based macroeconomic model and our optimal portfolio construction algorithm, we create a novel macroeconomic asset-trading framework.

An Aco-Inspired, Probabilistic, Greedy Approach To The Drone Traveling Salesman Problem, Jessica Houseknecht

Senior Honors Theses

In recent years, major companies have done research on using drones for parcel delivery. Research has shown that this can result in significant savings, which has led to the formulation of various truck and drone routing and scheduling optimization problems. This paper explains and analyzes a new approach to the Drone Traveling Salesman Problem (DTSP) based on ant colony optimization (ACO).

The ACO-based approach has an acceptance policy that maximizes the usage of the drone. The results reveal that the pheromone causes the algorithm to converge quickly to the best solution. The algorithm performs comparably to the MIP model, CP …

Applications Of Optimization Modeling In Multi-Disciplinary Engineering Research, Anton F. Astner, Ekramul Haque Ehite, Yang Li, Colin Sasthav

Biosystems Engineering and Soil Science Publications and Other Works

Optimization modeling is the process of selection of the best solution to a design problem using predetermined constraints from a set of prospective solutions. Increased computing power has made optimization solvers readily available for business/research needs. For example, Microsoft Excel has a simple, but robust solver. Such solvers can model linear, nonlinear, and integer programming problems that are limited in size. This study shows the use of the optimization model solvers in various research contexts.

On Accounting For Equipment-Control Interactions In Economic Model Predictive Control Via Process State Constraints, Helen Durand

Chemical Engineering and Materials Science Faculty Research Publications

Traditionally, chemical processes have been operated at steady-state; however, recent work on economic model predictive control (EMPC) has indicated that some processes may be operated in a more economically-optimal fashion under a time-varying operating policy. It is unclear how time-varying operating policies may impact process equipment, which must be investigated for safety and profit reasons. It has traditionally been considered that constraints on process states can be added to EMPC design to prevent the controller from computing control actions which create problematic operating conditions for process equipment. However, no rigorous investigation has yet been performed to analyze whether, when a …

Detecting Special-Cause Variation 'Events' From Process Data Signatures, Timothy M. Young, Olga Khaliukova, Nicolas André, Alexander Petutschnigg, Timothy G. Rials, Chung-Hao Chen

Electrical & Computer Engineering Faculty Publications

The ability to detect the special-cause variation of incoming feedstocks from advanced sensor technology is invaluable to manufacturers. Many on-line sensors produce data signatures that require further off-line statistical processing for interpretation by operational personnel. However, early detection of changes in variation in incoming feedstocks may be imperative to promote early-stage preventive measures. A method is proposed in this applied study for developing control bands to quantify the variation of data signatures in the context of statistical process control (SPC). Control bands based on pointwise prediction intervals constructed from the Bonferroni Inequality and Bayesian smoothing splines are developed. Applications using …

Technological Cooperation Network In Biotechnology Analysis Of Patents With Brazil As The Priority Country, Cristiano Goncalves Pereira, Rodrigo Ribeiro Da Silva, Joao Ricardo Lavoie, Geciane Silveira Porto

Engineering and Technology Management Faculty Publications and Presentations

Purpose – The establishment of partnerships between companies, government and universities aims to enhance innovation and the technological development of institutions. The biotechnology sector has grown in recent years mainly driven by its cooperative business model. Compared to other countries, this sector is slowly advancing in Brazil, with delays in science, technology and innovation, especially in the private sector. This paper aims to examine, through social network analysis, the collaborative networks between institutions that filed patents in biotechnology – medicinal preparations from plants – whose inventions had Brazil as the priority country. Design/methodology/approach – The study of technological cooperation using …

A Multi-Response Optimization For Isomerization Of Light Naphtha, Donia Abdel Nasser Fathy, Moustafa A. Soliman

Chemical Engineering

Isomerization process is considered one of the main processes used to produce high octane rating gasoline with improved environmental conditions and less emissions. The main keys of performance in isomerization units are the product yield, paraffin isomerization number (PIN) and octane number (RON). In this article we present a multi-response optimization strategy for an industrial naphtha continuous isomerization-process that aims to maximize RON, PIN and yield. Data of 53-runs including feed compositions as well as operating conditions; reactor temperature, benzene content, liquid hour space velocity, feed PIN, hydrogen to hydrocarbon ratio, feed octane number, C7+ content, inlet reactor temperature and …

Foundations For A Game Theoretic Framework For Agile Acquisition, Scott Rosen, Kelly Horinek, Alexander Odeh, Les Servi, Andreas Tolk

VMASC Publications

This article investigates the concept of developing a game theoretic framework that is based on the application of buyer and seller utility functions to support the bidding process in government acquisition. The results of a literature survey of utility function approaches, with potential to provide a suitable foundation to a game theory framework for acquisition, are presented. The utility function methods found most promising were further adapted and tested: the Best-Worst method, the Multi-Swing Method, and Functional Dependency for Network Analysis. To test the scalability of the approach, the Best-Worst method is applied to a larger problem to show the …