Publications

J.A Jimenez, B. Kim, J. Fowler, G. Mackulak, Y.I. Choung, and D.J. Kim

This paper studies the operational logic in an inter-bay automated material handling system (AMHS) in semiconductor wafer fabrication. This system consists of stockers located in a two-floor layout. Automated moving devices transfer lots between stockers within the same floor (intra-floor lot transfer) or between different floors (inter-floor lot transfer).

J.A. Jimenez, G.T. Mackulak, and J.W. Fowler

This paper identifies a method for classifying a fab model by the level of capacity detail, the level of AMHS detail, or the level of capacity/AMHS detail. Within the capacity/ AMHS modeling level, our method further differentiates between detailed integrated capacity/AMHS models and abstract coupled capacity/AMHS models.

S. Villarreal, J.A. Jimenez, T. Jin, and M. Cabrera-Rios

The study seeks to design a grid-connected DG system that is capable of providing the necessary electricity for wafer fabs. Simulation-based optimization algorithm was applied to determine the equipment type and capacity aiming to minimize the DG lifecycle cost.

D. Nazzal, J.A. Jimenez, H. Carlo, A. Johnson, and V. Lasrado

This paper proposes a queueing-based analytical model useful in the design of closed-loop conveyor-based automated material handling system (AMHS), which has been identified as an effective material handling alternative in next-generation semiconductor wafer fabrication facilities.

J.S. Park, S.J. Lee, J.A. Jimenez, S. K. Kim, and J.W. Kim

This article aims to integrate the indoor positioning technology with a specialized user application, which allows the users to define what kinds of data should be collected and how the raw data should be transformed.

Jesus A. Jimenez

This article presents the opportunities and challenges of digital twin applications for manual material handling systems.

Francis Mendez; David Wierschem; Jesus A. Jimenez

Geovanni Hernandez; Damian Valles; David C. Wierschem; Rachel M. Koldenhoven; George Koutitas; Francis A. Mendez; Semih Aslan; Jesus A. Jimenez

This paper evaluates machine learning techniques, based on Recurrent Neural Networks (RNN), to evaluate the fatigue factor caused by repetitive motions.

Jesus A. Jimenez ; Alexander Grosser ; Charitha Adikaram ; Victoria Davila ; Robert Wright ; Michael Bell

In this paper, AMHS productivity detractors affecting small lot manufacturing are studied, including the track layout, number of vehicles, empty vehicle management rules, number of stockers, stocker capacity, among others.

Soondo Hong; Andrew Johnson; Hector Carlo; Dima Nazzal; Jesus A. Jimenez

This paper proposes several heuristics to optimize the location of crossovers in a conveyor-based AMHS for semiconductor wafer fabs. The heuristics determine the locations of special conveyor path segments (cross overs) to minimize relevant capital and operating costs.

Victor Santana-Viera; Jesus Jimenez; Tongdan Jin

This paper covers the modelling and implementation of an interruptible/curtailable DR programme participated by a manufacturer that possesses onsite renewable generation units.

Timm Ziarnetzky ; Lars Mönch ; Thulasi Kannaian ; Jesus Jimenez

In this paper, we consider elements of a sustainable and distributed generation system for a wafer fab. The objective function of the production planning formulation contains production-related costs, cost for energy from the substation, and penalty costs when a renewable energy penetration is not reached.

Yue Li; Jesus A. Jimenez; Cecilia Temponi; Francis Mendez

In this paper, the association rules mining algorithm is applied to the distribution center’s order picking processes. The framework creates itemsets of stock-keeping units (SKU) frequently found in the same order and positions an item near the rest of the members of the family to reduce the order picking time. This paper is under review.

Junwoo Kim; Francis Mendez; Jesus A. Jimenez

This working paper considers heuristic approaches to assign stock keeping units (SKU) to individual slots in the distribution center. Two novel strategies are proposed for slot selection and frequent itemset grouping. The former is used to find the most suitable slot for a single SKU, while the latter is for sequencing SKUs in the appropriate order.

Jesus Jimenez; Abhimanyu Sharotry; and Francis A. Mendez

This paper explores challenges in warehouse operations, focusing on forklift operators and their role in meeting customer demand. Forklifts pose significant safety concerns with thousands of work-related injuries and fatalities recorded annually. The study aims to develop a methodological framework integrating factors like energy consumption, training, the Internet of Things, ergonomics, and human factors such as work fatigue to enhance forklift operator efficiency and safety.

T. Caroll; G. Hernandez; G. Koutitas; D. Wierschem; F. Mendez; D. Vallez; S. Aslan; R. Koldenhoven; and J. Jimenez

This paper presents two Inverse Kinematics (IK) algorithms for digital twin Augmented Reality (AR) applications, evaluating their performance with a Motion Capture (MoCap) system. The algorithms model motion with up to 9 and 38 points on the human body, respectively. The study emphasizes the significance of accuracy, especially in lifting motions, aligning with Digital Twin (DT) concepts in Industry 4.0 scenarios.

David C. Wierschem; Jesus A. Jimenez; and Francis A. Mendez

This manuscript introduces a motion capture-based method for manufacturing time and motion studies. The human motion analytics system utilizes motion capture technology to collect and analyze data from repetitive physical motions in manufacturing. It enables the isolation of basic motions for analysis using statistical process control and data analytics, identifying patterns and deviations from those patterns.

Abhimanyu Sharotry; Jesus A. Jimenez; David Wierschem; Francis A. Mendez; Rachel M. Koldenhoven; Damian Valles; George Koutitas; and Semih Aslan

This research presents a digital twin concept and prototype for human operators in the material handling industry. Utilizing a simulation-based framework with three modules, including Data Collection and Digital Twin, a motion capture system captures simulated material handling activities. The digital twin offers real-time feedback to address factors causing operator fatigue during repetitive lifting tasks.

Geovanni Hernandez; Damian Valles; David C. Wierschem; Rachel M. Koldenhoven; George Koutitas; Francis A. Mendez; Semih Aslan; Jesus Jimenez

In the context of Industry 4.0, this research explores the impact of repetitive motions on workers in the material handling industry, leading to fatigue and musculoskeletal disorders. Using infrared cameras, time-stamped motion data is collected during actions like lifting, with 39 reflective markers providing detailed coordinates. The study employs a Recurrent Neural Network (RNN)-based machine learning model to assess the fatigue factor induced by these repetitive motions.

By Abhimanyu Sharotry; Jesus A. Jimenez; Francis A. Mendez; David Wierschem; Rachel M. Koldenhoven; and Damian Valles

This research introduces a Digital Twin (DT) framework for analyzing fatigue during manual material handling (MMH) lifting activities, focusing on back, elbow, and knee joint angles. Using the dynamic time warping (DTW) algorithm, the study's preliminary results with two male subjects under an optical motion capture system demonstrate the model's efficiency in assessing biomechanical fatigue and emphasize the need for personalized DTs in MMH environments.