Now showing 1 - 8 of 8
  • Some of the metrics are blocked by your 
    Item type:Publication,
    A Comparative Study of Unbalanced Production Lines Using Simulation Modeling: A Case Study for Solar Silicon Manufacturing
    (2022-01-01)
    Cheng, Chen Yang
    ;
    Li, Shu Fen
    ;
    Lee, Chia Leng
    ;
    ;
    In the solar silicon manufacturing industry, the production time for crystal growth is ten times longer than at other workstations. The pre-processing time at the ingot-cutting station causes work-in-process (WIP) accumulation and an excessively long cycle time. This study aimed to find the most effective production system for reducing WIP accumulation and shortening the cycle time. The proposed approach considered pull production systems, and the response surface methodology was adopted for performance optimization. A simulation-based optimization technique was used for determining the optimal pull production system. The comparison between the results of various simulated pull production systems and those of the existing solar silicon manufacturing system showed that a hybrid production system in which a kanban station was installed before the bottleneck station with a CONWIP system incorporated for the rest of the production line could reduce the WIP volume by 26% and shorten the cycle time by 16% under the same throughput conditions.
  • Some of the metrics are blocked by your 
    Item type:Publication,
    Integrating Spatial Risk Factors with Social Media Data Analysis for an Ambulance Allocation Strategy: A Case Study in Bangkok
    (2022-08-01) ; ;
    Boonkul, Klongkwan
    ;
    Chaicharoenwut, Pakinai
    ;
    Nilsang, Suriyaphong
    Emergency medical service (EMS) base allocation plays a critical role in emergency medical service systems. Fast arrival of an EMS unit to an incident scene increases the chance of survival and reduces the chance of victim disability. However, recently, the allocation strategy has been performed by experts using past data and experiences. This may lead to ineffective planning due to a lack of consideration of a recent and relevant data, such as disaster events, population density, public transportation stations, and public events. Therefore, we propose an approach of the integration of using spatial risk factors and social media factors to identify EMS bases. These factors are combined into a single domain by using the kernel density estimation technique, resulting in a heatmap. Then, the heatmap is used in a modified maximizing covering location problem with a heatmap (MCLP-Heatmap) to allocate ambulance base. To acquire recent data, social media is then used for collecting road accidents, traffic, flood, and fire incidents. Additionally, another data source, spatial risk information, is collected from Bangkok GIS. These data are analyzed using the kernel density estimation method to construct a heatmap before being sent to the MCLP-heatmap to identify EMS bases in the area of interest. In addition, the proposed integrated approach is applied to the Bangkok area with a smaller number of EMS bases than that of the existing approach. The simulated results indicated that the number of covered EMS requests was increased by 3.6% and the number of ambulance bases in action was reduced by approximately 26%. Additionally, the bases defined by the proposed approach covered more area than those of the existing approach.
  • Some of the metrics are blocked by your 
    Item type:Publication,
    Multiple-performance optimization for human-robot collaboration: A translation motion in a tele-sandblasting maintenance system
    (2016-01-01) ; ; ;
    Limnararat, Sunpasit
    Human-robot collaboration is a vital part of teleoperation systems. Determining the design parameters satisfying the optimal human performance is very important in the design of a teleoperation system for a specific task. Specifically, to thoroughly represent human performance for a task, multiple performance measures in a teleoperation system are evaluated. The experiment was also conducted on a mixed-reality tele-sandblasting system which is setup to study 2D-motion translation in tele-sandblasting task. Then, identifying the design setting to satisfy the optimal measures are difficult due to conflicts among them. Therefore, this paper presents a multipleperformance optimization using a desirability function. The results provide the range of setting condition promoting the optimal human performance measures. © IEOM Society International.
  • Some of the metrics are blocked by your 
    Item type:Publication,
    Variation minimization in tele-sandblasting system: The effect of human-arm movement error
    (2018-08-14) ;
    Attavanish, Pornsak
    ;
    ;
    Limnararat, Sunpasit
    ;
    In tele-sandblasting task, human arm movement is a critical source of producing variation in position of sandblasting nozzle resulting in high operating cost and low productivity. Each operator behaves differently leading to unpredictable movements. Skilled operators are able to reduce the variation; however, developing skills requires a training period. In this paper, we proposed a new approach which is the use of a novel operator's arm movement pattern incorporated with a Kalman filter to reduce the effect of human-arm movement error. A virtual tele-sandblasting system is used to validate our approach. The experimental results verify that our proposed approach is able to significantly reduce the effect of human arm movement error. The approach helps operators to perform the task more comfortably and takes short training time.
  • Some of the metrics are blocked by your 
    Item type:Publication,
    A variation reduction in the tele-abrasive system: A study of human movement
    (2021-08-02) ; ;
    Chaiprapat, Supapan
    In a tele-abrasive task, it is principally human arm movements that cause variation in the position of the abrasive nozzle, thereby resulting in high operating costs and low productivity. It is difficult to design a system that can minimize the variation that accrues from operators behaving differently, which is difficult to predict. Although skilled operators can reduce this variation, becoming a skillful operator requires a lengthy training period. In this work, a two-stage variation streaming technique was used to extract variation sources in a tele-abrasive system. Furthermore, we propose an integrated human–computer approach to control variation in these systems—an approach that applies an innovative human arm movement pattern incorporated with a Kalman filter into a standard system. A virtual tele-abrasive system was used to validate our approach. Furthermore, compared with conventional systems, the proposed approach will help operators to perform abrasive tasks more comfortably and require a shorter training period.
  • Some of the metrics are blocked by your 
    Item type:Publication,
    Crowdsourced adaptive vehicle routing framework for Last-Mile delivery in dynamic traffic environments
    (2025-01-01)
    Dahlan, Ahmad Faisal
    ;
    Cheng, Chen Yang
    ;
    Sae-chai, Pornkanok
    ;
    ;
    Last-Mile Delivery (LMD) operations are significantly impacted by real-time traffic disruptions, leading to delays and increased costs. While traditional vehicle routing problem (VRP) model struggle to adapt to dynamic traffic environments, crowdsourced data from social media platforms presents a valuable source of real-time traffic data. This research proposes Crowdsourced Adaptive Vehicle Routing Framework (CAVRF) that integrates crowdsourced social media data into the VRP model for enhanced efficiency. The framework employs a machine learning model to classify tweets based on impact severity and effectively filtering relevant traffic information. Furthermore, a mathematical model known as the Adaptive Traffic VRP (AT-VRP) has been developed to accommodate the integration of social media data with the VRP model. The framework’s effectiveness is demonstrated through a case study using a package delivery network in Jakarta with various levels of traffic disruptions. The findings suggest that integrating crowdsourced social media data into AT-VRP significantly improves efficiency by avoiding any road closure. CAVRF offers a cost-effective and efficient solution to the dynamic challenges inherent in LMD.
  • Some of the metrics are blocked by your 
    Item type:Publication,
    Investigating multiple human performance measures in teleoperation task: A translation task in a tele-sandblasting maintenance system
    (2018-05-01) ; ;
    Cheng, Chen Yang
    ;
    ;
    Limnararat, Sunpasit
    In sandblasting tasks for complex steel structure maintenance, teleoperation is required to keep humans away from occupational risk and hazard. On the other hand, teleoperation typically degrades system-human performances, resulting in poor product quality and must be designed such that the performances remain as high as possible. However, designing the teleoperation system regarding to a single performance measure may lead to an improper design. In this article, we propose two novel loss-function-based human-performance measures to incorporate with a widely used performance measure, movement time, to thoroughly represent performance: unfinished surface and damaged surface. We aim to investigate the effects of two main design parameters, viewing distance and path width. The results show that only path width is significant for overall performances. Furthermore, the effect of gender is significant such that men outperform women in cleaning the surface. Finally, the optimal setting conditions are suggested to achieve their optimal performances.
  • Some of the metrics are blocked by your 
    Item type:Publication,
    Minimizing multi-stage system variation using Kalman filter for a tele-sandblasting system
    In teleoperation systems which generally require human-robot collaboration to operate the tasks, task performances suffer from uncontrollable factors, i.e., human skills, time delay, and robot movement errors. To incorporate with this situation, the system must be designed to withstand those factors' effects. Recently, system robustness has become an essential issue for designing manufacturing systems. In this paper, we present a robust design to control the variation for multi-stage tele-sandblasting system. The objective is to locate the sandblasting nozzle at desired positions while minimizing system variation. A multi-stage variation estimation model with Kalman filter is proposed to estimate and control the system variation over time. The results show that our approach significantly decreases tele-sand blasting system variation.