Operational Research Commons^™

A Random Forest-Based Q-Learning Algorithm: Toward Interpretable Artificial Intelligence, Victor R. Rae

Theses and Dissertations

A growing demand exists for interpretable artificial intelligence models, leading to extensive research efforts to enhance the explainability and transparency of policies generated by reinforcement learning (RL) methods. This research develops random forest-based RL algorithms as a logical progression in this academic pursuit. The algorithms are evaluated using three standard benchmark environments from OpenAI gym — CartPole, MountainCar, and LunarLander — and compared to implementations of the Deep Q-learning Network (DQN) and Double DQN (DDQN) algorithms for various metrics, including performance, robustness, efficiency, and interpretability. The random forest-based algorithms exhibit superior performance to both neural network-based algorithms in two out …

Knowledge Management Modeling And Decision Analysis For Usmepcom, Luke G. Wunderlich

Theses and Dissertations

This thesis explores the adoption of Value-Focused Thinking (VFT) in enhancing the Knowledge Management (KM) program at USMEPCOM, aiming to align decision-making with the organization’s values and goals. Through evaluating the current knowledge flow and policy drafts, it proposes categorizing command messages, establishing a centralized information repository, and scheduling a daily order release to improve information accessibility and operational readiness. Although no alternative offers a perfect solution, implementing Command Message Categorization is expected to significantly enhance operational efficiency and prepare USMEPCOM for future challenges.

Training Schedule For The 56th Maintenance Group, Samantha K. O'Rourke

Theses and Dissertations

The 56th Equipment Maintenance Squadron (56 EMS) provides equipment maintenance and back shop maintenance for the F-35 Joint Strike Fighter. The squadron executes thousands of sorties and flight hours annually. This operations tempo requires maintenance to prevent equipment failures, minimization of aircraft downtime, insurance of safety and compliance, and training of maintenance personnel. The squadron incorporates periodic training sessions to train maintenance personnel skills needed by airmen. This research investigates the optimization of these training sessions employing mixed integer programming (MIP). A multi-objective MIP model is developed to address the complex needs of various training activities, such as: training regiments, …

An Assignment Model For Lateral Transfers Matching Base Repair Facilities To Xf3 Coded Nsns Requiring Repair, George D. Valaika

Theses and Dissertations

This research addresses challenges in efficiently distributing reparable National Stock Numbers (NSNs) to base-level repair facilities, aiming to ease strain on depot resources. It establishes a network integrating bases with similar repair capabilities for NSNs and allocates NSNs to balance repair capacities. Drawing from USAF reparable inventory modeling and inventory management theory, it generates data mimicking historical data to maximize total expected part repairs by assigning NSNs based on the best percentage of base repair (PBR).

Enhancing Port Efficiency And Lead Time Reduction Through Predictive Analysis: A Case Study Of Container Management At Khalifa Bin Salman Port, Abdulaziz A. Aljalahma

Theses and Dissertations

Khalifa bin Salman Port (KBSP), a key pillar in Bahrain's maritime infrastructure, is the focal point of this study, highlighting the significant role of predictive analytics in optimizing port operations. This thesis analyzes container throughput data from 2017 to 2022, provided by Bahrain's Ministry of Transportation database. This data forms the basis for forecasting the 2023 throughput. The study thoroughly compares these predictions with the actual 2023 data, assessing the predictive model's accuracy. The findings underscore the importance of predictive analytics in strategic decision-making for port management, focusing on enhancing operational efficiency and reducing lead times. This research offers a …

On Intrinsic Dimensionality Of Data Sets And Neural Networks, Ori Chachmo

Theses and Dissertations

The concept of Intrinsic Dimensionality (ID) is of special interest in the field of Neural Networks (NNs) since it promotes both (a) a deeper understanding of the underlying mechanisms, and (b) embraces parsimonious modeling (that is, building the right-sized model for the task) with associated benefits to processing speed and storage requirements. This thesis explores the concept of ID via two separate, but related, questions. First, we study the potential of NN ID prediction by exploiting easily obtained quantities measured on the data. We then explore NN ID as an independent concept by comparing the results of different methods for …

Advanced Intermediate Manufacturing (Aim) Supply Chain Concepts Leading To Reduced Lead Times And Improved Responsiveness, Eric S. Draudt

Theses and Dissertations

This thesis investigates the optimization of the supply chain for key aircraft components, focusing on the implementation of Advanced Intermediate Manufacturing (AIM) production facilities. Utilizing anyLogistix, the study compares the current supply chain model based on Supply Chain Operations Wing (SCOW) data with various AIM production facility configurations: single, dual, quadruple, and three utilization-driven models (high, medium, and low). The findings demonstrate that integrating AIM production facilities significantly reduces lead times, with even a single facility dramatically cutting down the lead time from over 800 days to approximately 104 days. The utilization models further provide insights into operational flexibility under …

2033 Digital Modernization At Usmepcom: A Strategic Analysis Of Future Military Applicant Processing, William A. Clay

Theses and Dissertations

This research examines the projected 2033 applicant processing scenario considering the digital modernization efforts of the United States Military Entrance Processing Command (USMEPCOM). The study evaluates the necessary modifications to current processes, with a particular focus on the influence of two key information technology systems, the MEPCOM Integrated Resource System (MIRS) 1.1 and the Military Health System (MHS) Genesis, on manpower at a Military Entrance Processing Station (MEPS). In doing so, the study establishes baseline processing metrics for assessing these impacts. By utilizing discrete event simulation modeling and leveraging current literature, the study proposes strategies for incorporating technological advancements into …

Systematic Review Of Supply Chain Control Tower Critical Success Factors And Resilience Effects, Clay H. Chaffin

Theses and Dissertations

Supply chain control towers (SCCTs) are emerging as a vital component of modern supply chain management (SCM); however, research on SCCTs is limited and disjointed. This paper aims to uncover the critical success factors (CSFs) necessary for high-performing SCCTs, their relationship to the enablers and phases of supply chain resilience (SCRES), and the underlying theoretical framework of this relationship.

Federated Medical Scoring Systems, Jacob F. Bryant

Theses and Dissertations

Federated Learning (FL) is a recent framework of machine learning implementation that trains models on a distributed network of clients as opposed to housing and analyzing this data centrally. This has data communication and practical data privacy advantages, the latter of which is particularly attractive to the medical community where patient privacy is closely safeguarded. We apply FL to a family of sparse linear integer models called Medical Scoring Systems (MSSs). We create a novel methodology for creating these MSSs in a simulated federated environment that involves an lo constrained Logistic Regression (LR), loss-surface examination, and rounding procedure. We tested …

An Analysis Of China’S Perceived Geographic Locations Of Interest By Use Of Value Informed Facility Location Models, Layton C. Hedge

Theses and Dissertations

This research examines China and derives insights specific to it and the First Island Chain and the Second Island Chain. In doing so, this research demonstrates a methodology to examine other competitors and their geostrategic interests. In the first phase of analysis, it develops a value hierarchy to depict objectives within subregions of the area of interest and considers four alternative weightings of the value hierarchy. In the second phase of analysis, it applies four location-covering models to assess how the competitor would emplace a range of limited resources to deter and/or control points of interest. Results indicate that land-based …

A Multi-Objective Approach To Optimal Deployment Policies For Wireless Sensor Networks Using Drop Points, Noah E. Fox

Theses and Dissertations

This research addresses the development of deployment policies for aerially dropped sensors in a wireless sensor network (WSN). Multi-objective genetic algorithm (GA) and simulated annealing meta-heuristic techniques, along with Monte Carlo simulation are used to identify policies with the aim of maximizing coverage and minimizing the number of sensors deployed. The policies developed from these techniques are then compared against uniform sensor distribution, as well as initial deployment policies that focus sensors in the center and edge of the region, as well as evenly deployed over the region. A total of 29 non-dominated policies were identified from the GA and …

Analysis And Visualization Of Military Convoy And Supply Utilization In Support Of State-Specific Freight Plans, Madison E. Hofmann

Theses and Dissertations

Researching the United States military’s use of highways and interstates is necessary for the allocation of federal infrastructure spending. As of today, there is no established method, tool, or process routinely utilized by the Surface Deployment and Distribution Command to effectively show a system-wide view of military convoy and supply route usage across CONUS. This research advances this endeavor by providing a by-state characterization of interstates and major highways in 2022, categorized by the volume of military freight they support. Some notable methodologies used to conduct the analyses are the shortest path problem, map matching algorithms, and Global Positioning System …

A Reinforcement Learning Approach To The 2v2 Beyond Visual Range Air Combat Maneuvering Problem, Jacob J. Pike

Theses and Dissertations

This research examines a 2v2 air combat maneuvering problem (ACMP) in a Beyond Visual Range (BVR) environment. A discrete-time, infinite-horizon Markov Decision Process (MDP) model represents the BVR-ACMP, seeking to determine high-quality policies for a pair of autonomous aircraft to execute tactical maneuvers and firing decisions. The Advanced Framework for Simulation, Integration, and Modeling (AFSIM) characterizes the complex six-degree of freedom (6-DOF) aircraft operations, encompassing kinematics, sensors, and weapons. Given the high dimensionality and continuous nature of the state and decision variables, a deep reinforcement learning (RL) solution approach is adopted wherein the value function is approximated via a Neural …

Navigating Complex Environments: A Comparative Study Of Shortest Path Algorithms For Military A2ad And Civilian Obstacle Avoidance, Ebony N. Williams

Theses and Dissertations

This thesis investigates advanced navigation in complex environments for urban and military applications, focusing on overcoming obstacles through algorithms like Dijkstra's. It highlights the role of adaptable cost functions in customizing strategies for different scenarios. The research identifies effective algorithm-cost function combinations, improving route planning and safety in civilian and defense sectors. It advances pathfinding knowledge and sets the groundwork for future enhancements with Python simulations and AFSIM.

U.S. Army Cadet Command Branch Prediction Model, Daniel M. Krizan

Theses and Dissertations

The current system for providing US Army ROTC cadets their branches leaves significant uncertainty until the final pronouncement of branch assigned. This uncertainty can be alleviated by providing a prediction model for cadets to input personal data and desired branch to identify likelihood of receiving the request. This thesis produces a machine learning model capable of producing branch prediction for cadets.

Assessing Adoption Barriers Of Sustainable Packaging In Egypt, Carol Ramses Morgan

Theses and Dissertations

Sustainable packaging has become an essential part of business decisions and corporate directions. With the rise of environmental damages due to improper waste management and unsustainable practices, businesses have a major responsibility to analyze their products’ life cycles and redesign them with sustainability in mind. Applying sustainable packaging could save companies large amounts of resources, therefore cutting costs, while also achieving the legal and social duty as a corporation towards society and the environment. Many developing countries, with specific focus on Egypt, have recently focused on legislative and corporate decisions in order to encourage more sustainable practices. Egypt’s new Waste …

Containerization Of Seafarers In The International Shipping Industry: Contemporary Seamanship, Maritime Social Infrastructures, And Mobility Politics Of Global Logistics, Liang Wu

Dissertations, Theses, and Capstone Projects

This dissertation discusses the mobility politics of container shipping and argues that technological development, political-economic order, and social infrastructure co-produce one another. Containerization, the use of standardized containers to carry cargo across modes of transportation that is said to have revolutionized and globalized international trade since the late 1950s, has served to expand and extend the power of international coalitions of states and corporations to control the movements of commodities (shipments) and labor (seafarers). The advent and development of containerization was driven by a sociotechnical imaginary and international social contract of seamless shipping and cargo flows. In practice, this liberal, …

Characterizing Linearizable Qaps By The Level-1 Reformulation-Linearization Technique, Lucas Waddell, Warren Adams

Faculty Journal Articles

The quadratic assignment problem (QAP) is an extremely challenging NP-hard combinatorial optimization program. Due to its difficulty, a research emphasis has been to identify special cases that are polynomially solvable. Included within this emphasis are instances which are linearizable; that is, which can be rewritten as a linear assignment problem having the property that the objective function value is preserved at all feasible solutions. Various known sufficient conditions for identifying linearizable instances have been explained in terms of the continuous relaxation of a weakened version of the level-1 reformulation-linearization-technique (RLT) form that does not enforce nonnegativity on a subset …

Natural Language Processing Analysis Of Online Reviews For Small Business: Extracting Insight From Small Corpora, Benjamin J. Mccloskey, Phillip M. Lacasse, Bruce A. Cox

Faculty Publications

Receiving and acting on customer input is essential to sustaining and growing any service organization, particularly a small family business whose livelihood depends on strong relationships with its customers. The competitive advantage offered by advanced analytical approaches for supporting decisions is not trivial, and enterprises across virtually all domains of society are investing heavily in this emerging discipline. Natural Language Processing (NLP) is a subset of computer science that employs computational approaches to analyze human language; it is effective at extracting insight from text data but frequently requires large corpora to train its models, in the scale of thousands or …

Application Of Learning Processes For Improving Last-Mile Logistics Optimization At Scale, Seyedeh Shaghayegh Rabbanian

LSU Doctoral Dissertations

The escalating demands of omnichannel retailing, rapid urbanization and shifting customer behaviors have propelled last-mile vehicle routing logistics to the forefront of research. This last-mile phase, recognized as a significant contributor to costs and pollution in the supply chain, necessitates efficient route optimization to minimize expenses and environmental impact. This research delves into machine learning based techniques for solving large-scale Vehicle Routing Problem (VRP), a fundamental concern in last-mile logistics, aiming to optimize delivery vehicle routing amidst diverse customer nodes and operational constraints. Three primary research subproblems are analyzed: utilizing machine learning for constructive solutions, Variable Neighborhood Search (VNS) metaheuristic, …

Operations Research In Civil And Environmental Engineering, Nicholas Lownes

Open Educational Resource

The purpose of this text is introduce fundamental operations research techniques to the civil and/or environmental engineering student, providing a broad background in linear programming, integer programming and network optimization. The material is presented in such a manner so that the student does not need an extensive background in operations research or or linear algebra. Applications include transportation engineering, project management and general civil and environmental engineering applications.

What Can We Learn From A Co-Creation Journey For A Quick Scan Digital Transformation Maturity Assessment Tool For Development Ngos?, Anand Sheombar

Journal of International Technology and Information Management

This paper describes the approach and lessons learned from a co-creation process with Dutch development NGOs to create a practical and easy-to-use assessment tool for practitioners to assess the organisation's maturity level of digital transformation. For this study, we applied a design science research methodology, specifically a six-step co-creation approach suitable for developing maturity models. The digital maturity assessment tool (quick scan) created is a domain- specific digital transformation maturity tool for development NGOs rather than a generally applicable tool. This artefact was evaluated using an eight-point Requirements framework for the development of digital maturity assessment tools. By developing a …

An Algorithm Based On Priority Rules For Solving A Multi-Drone Routing Problem In Hazardous Waste Collection, Youssef Harrath Dr., Jihene Kaabi Dr.

Research & Publications

This research investigates the problem of assigning pre-scheduled trips to multiple drones to collect hazardous waste from different sites in the minimum time. Each drone is subject to essential restrictions: maximum flying capacity and recharge operation. The goal is to assign the trips to the drones so that the waste is collected in the minimum time. This is done if the total flying time is equally distributed among the drones. An algorithm was developed to solve the problem. The algorithm is based on two main ideas: sort the trips according to a given priority rule and assign the current trip …

การจัดเส้นทางการเดินรถที่มีหลายจุดกระจายสินค้าโดยพิจารณารอบเวลาการวางแผน, วัสพล ตรีธนวัต

Chulalongkorn University Theses and Dissertations (Chula ETD)

การศึกษานี้มุ่งเน้นการแก้ปัญหาการจัดส่งอาหารแบบพลวัต โดยที่คำสั่งซื้อเข้ามาในระบบแบบพลวัตและต้องจัดส่งถึงลูกค้าภายในกรอบเวลาที่กำหนด โดยใช้ยานพาหนะที่มีความจุจำกัดสำหรับการจัดส่ง เป้าหมายหลักคือการลดระยะทางในการขนส่งทั้งหมดให้น้อยที่สุด พร้อมกับตอบสนองความต้องการของลูกค้าได้ทันเวลา ผู้เขียนได้นำเสนอวิธีการแก้ปัญหาที่ประกอบด้วย 2 ขั้นตอนหลัก คือ 1. การจัดกลุ่มคำสั่งซื้อ คือทำการจัดกลุ่มคำสั่งซื้อตามเวลาที่คำสั่งซื้อเข้ามาและกรอบเวลาการจัดส่ง และ 2. การปรับเส้นทางสำหรับแต่ละกลุ่มคำสั่งซื้อ จะทำการคำนวณเส้นทางการจัดส่งที่เหมาะสมที่สุด โดยใช้โมเดลปัญหาการจัดเส้นทางการขนส่งแบบมีกรอบเวลา วิธีการนี้ได้รับการประเมินโดยการทดลอง ซึ่งแสดงให้เห็นว่ากรอบเวลาการตัดสินใจ หรือช่วงเวลาที่ใช้ในการจัดกลุ่มคำสั่งซื้อ มีผลกระทบต่อผลลัพธ์ หากกรอบเวลาการตัดสินใจแคบลง จะต้องใช้จำนวนยานพาหนะที่มากขึ้นเมื่อเทียบกับกรอบเวลาที่กว้างขึ้น แต่จะช่วยลดเวลาเฉลี่ยที่ลูกค้าต้องรอได้ ในขณะที่กรอบเวลาที่กว้างขึ้น ช่วยให้สามารถรวมคำสั่งซื้อหลายรายการไว้ในเส้นทางการจัดส่งเดียวกันได้มากขึ้น ซึ่งอาจลดต้นทุนระยะทางการเดินทางลงได้ อย่างไรก็ตาม หากกรอบเวลากว้างเกินไป อาจส่งผลให้ระยะทางเพิ่มขึ้น เนื่องจากช่วงเวลาระหว่างการตัดสินใจและเวลาจัดส่งที่กำหนดไว้น้อยเกินไป จนทำให้เกิดการเพิ่มรอบขนส่งอาหาร

การจัดสมดุลสายการประกอบแบบขนานหลายวัตถุประสงค์ที่ทำงานโดยพนักงานหลายทักษะและหุ่นยนต์, ธนภัทร์ จิตรศรีศักดา

Chulalongkorn University Theses and Dissertations (Chula ETD)

การจัดสมดุลสายการประกอบแบบขนานที่ประกอบด้วยพนักงานปกติ ผู้พิการ ผู้สูงอายุ และหุ่นยนต์ Cobot โดยการพิจารณาทุกฟังก์ชันวัตถุประสงค์ไปพร้อมๆกันจัดเป็นปัญหาเอ็นพีแบบยาก (NP-Hard) ที่มีความยุ่งยากและซับซ้อนของปัญหาดังนั้น จึงต้องพิจารณาใช้วิธีการแก้ปัญหาแบบฮิวริสติก (Heuristic) และเมตาฮิวริสติก (Meta-Heuristic) มาช่วยในการแก้ปัญหา งานวิจัยนี้ได้มีการนำเสนอพนักงานหลายทักษะซึ่งจะมีข้อจำกัดแตกต่างกันไป โดยจะมีพนักงานปกติ พนักงานผู้พิการ และพนักงานผู้สูงอายุ เพื่อจะดูว่าการใช้พนักงานประเภทต่างๆจะมีผลกระทบต่อประสิทธิภาพของสายการประกอบอย่างไร งานวิจัยนี้ใช้วิธีเชิงพันธุกรรมแบบการจัดลำดับที่ไม่ถูกครอบงำในการพัฒนาหาคำตอบของฟังก์ชันวัตถุประสงค์ ซึ่งเป็นการจำลองสายการประกอบโดยฟังก์ชันวัตถุประสงค์ประกอบด้วย 1) ประสิทธิภาพของสายการประกอบมากที่สุด 2) พลังงานไฟฟ้าที่หุ่นยนต์หรือ Cobot ใช้ในการทำงานน้อยที่สุด และ 3) ความแตกต่างด้านการใช้พลังงานของพนักกงงานน้อยที่สุด ผลการศึกษาแสดงให้เห็นว่าการใช้ Cobot สามารถลดภาระงานของพนักงาน โดยเฉพาะงานที่ต้องการความแม่นยำหรือทักษะเฉพาะทาง และเพิ่มความยืดหยุ่นให้กับสายการประกอบ นอกจากนี้ การกระจายภาระงานระหว่าง Cobot และพนักงานจะช่วยลดการใช้พลังงานเฉลี่ยต่อ Cobot และทำให้การใช้งานพลังงานของพนักงานมีความสมดุลมากขึ้น ส่งผลให้ความแปรปรวนของภาระงานลดลง และการจัดสมดุลพลังงานในสายการประกอบมีความสมดุลมากขึ้น กล่าวโดยสรุปก็คือ Cobot มีบทบาทสำคัญในการเพิ่มประสิทธิภาพและความยืดหยุ่นของสายการประกอบ พร้อมช่วยลดข้อจำกัดด้านแรงงานและพลังงานได้อย่างชัดเจน

Virtual Reality Of Labless Machining For Next Industrial Training, Ravee Bunduwongse

Chulalongkorn University Theses and Dissertations (Chula ETD)

This study aims to utilize Virtual Reality (VR) technology to develop an industrial training application with content focusing on Machining operation using lathe machine. The focus of the study is to present the content being taught in manufacturing laboratory classes about lathe machining operations in the virtual world. Development tools include Unity game engine and 3D modeling using Blender. Machining operations demonstrated within this application includes turning, facing, chamfering, grooving, internal and external threading. With 17 out of 18 operations represented in accordance to the actual teaching material, with only external threading deviating from applying threading using the lathe machine …

Virtual Reality Of Labless Welding For Next Industrial Training, Suphakit Anonglekha

Chulalongkorn University Theses and Dissertations (Chula ETD)

This research introduces an innovative Virtual Reality (VR) application designed to educate users on Welding operations. Its main goals include creating a realistic and immersive learning environment that is also safe. The development process involved the integration of multiple technologies, leveraging the Unity engine and 3D sculpting, all based on extensive research. With all of the type of weld works found in the welding laboratory represented, except the workpiece and electrode material, the VR application accuracy rating is calculated to 94%. The study's significance lies in its contribution to virtual education, especially in fields that require hands-on experience. The VR …

Algorithms For Coordinating Multiple Autonomous Vehicles Under Various Constraints With Emphasis On Workload Balancing, Abhishek Patil

Dissertations, Master's Theses and Master's Reports

This dissertation focuses on developing algorithms to solve the problem of coordinating multiple autonomous vehicles under various constraints, aiming to produce practical solutions for real-world applications. Built upon three journal publications addressing two coordination-related problems in different domains, this research document tackles the challenges of heterogeneity constraints and cable entanglement issues encountered by autonomous vehicle systems.

The first problem tackles task allocation and path planning for heterogeneous ground mobile vehicles operating in a 2D environment with asymmetric travel costs. By enhancing previous Primal-Dual approximation heuristic methods, novel techniques are introduced to manipulate dual variables and achieve balanced workload distribution, ultimately …

การประยุกต์เทคนิคเหมืองข้อความเพื่อตรวจจับความผิดพลาดในแบบฟอร์มคำขอผลิตชิ้นงานทางวิศวกรรม, โยทะกา เสนีย์วงศ์ ณ อยุธยา

Chulalongkorn University Theses and Dissertations (Chula ETD)

ในอุตสาหกรรมอิเล็กทรอนิกส์ที่มีการพัฒนาอย่างรวดเร็ว การจัดทำแบบฟอร์มคำขอสร้างผลิตภัณฑ์ (Engineering Build Request หรือ EBR) ที่ถูกต้องแม่นยำเป็นสิ่งสำคัญต่อการรักษาคุณภาพของผลิตภัณฑ์และการเพิ่มประสิทธิภาพของกระบวนการผลิต ข้อผิดพลาดในเอกสารเหล่านี้อาจส่งผลให้เกิดความเสียหายทางการเงิน เช่น ค่าปรับหรือการยกเลิกโครงการ การวิจัยนี้มีเป้าหมายเพื่อปรับปรุงกระบวนการตรวจสอบข้อผิดพลาดใน EBR โดยประยุกต์ใช้เทคนิคการทำเหมืองข้อความ(Text Mining)ผ่านโปรแกรมไพทอน (Python) พร้อมทั้งผสานเทคโนโลยีการรู้จำตัวอักษร (Optical Character Recognition: OCR) และกระบวนการประมวลผลข้อความอัตโนมัติ วิธีการศึกษาประกอบด้วยการเปรียบเทียบประสิทธิภาพของผู้ตรวจสอบเอกสารกับโปรแกรมอัตโนมัติโดยใช้การทดสอบ t-test แบบจับคู่ ผลการศึกษาพบว่า ระยะเวลาในการตรวจสอบของโปรแกรมอัตโนมัติ แตกต่างกันยังมีนัยสำคัญ (P-value < 0.001) เมื่อเปรียบเทียบกับกลุ่มผู้ตรวจสอบ โดยค่าเฉลี่ยระยะเวลาของโปรแกรมอัตโนมัติ คือ 0.0035 นาที และของผู้ตรวจสอบประมาณ 30 นาทีโดยเฉลี่ย และค่าความแม่นยำ (% Accuracy) ของโปรแกรมอัตโนมัติอยู่ที่ 99.48% และของผู้ตรวจสอบคือ 92.61%, 92.64% และ 92.72% ตามลำดับ จากการศึกษานี้สามารถเพิ่มประสิทธิภาพและลดระยะเวลาในการตรวจสอบเอกสารได้ ซึ่งจะช่วยลดต้นทุนและระยะเวลาการผลิตได้ดีขึ้น