Effective Material Handling System for JIT Automotive Production Line

Halim, Nurul Hayati Abdul; Yusuf, Noriah; Jaafar, Roseleena; Jaffar, Ahmed; Kaseh, Nur A in; Azira, Nur Nida

doi:10.1016/j.promfg.2015.07.044

Cited by 14 publications

(11 citation statements)

References 2 publications

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“…where represents the measured value of the th information expression form on the th index. Then, the entropy of the th index: (15) To 0 ≤ ≤ 1 , in (15), the coefficient should be calculated according to (16). When is all equal, = 1/ , and at this time, = = 1.…”

Section: F Comprehensive Evaluationmentioning

confidence: 99%

“…According to (16), when = 14, = 0.3789. Therefore, according to (15) Step 2. Calculating the weight coefficient of time and quantity According to (18), the weights of time and quantity can be calculated as follows: From the result of weights, the weight of time is greater than the weight of quantity.…”

Section: Comprehensive Evaluationmentioning

confidence: 99%

“…JIT system involves frequent shipments of smaller batch sizes from the supplier to the manufacturing enterprise [13], [14]. To achieve the objectives of JIT, the manufacturing enterprise must select the most appropriate supply chain network (an effective supply chain logistics system is necessary to support production processes [15]) for the reduction of total costs and waste of time [16].…”

Section: Introductionmentioning

confidence: 99%

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Supply Chain Logistics Information Quality Evaluation From Just-in-Time Perspective

et al. 2020

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In this paper, we seek to evaluate supply chain logistics information quality (SCLIQ) from the Just-In-Time (JIT) perspective. First, based on the analysis of SCLIQ, it is proposed that the SCLIQ evaluation should be combined with JIT philosophy. Second, based on SPC and information entropy method, an evaluation method of SCLIQ is presented. The statistical process control method (SPC) is adopted to evaluate the information quality of quantity and time respectively, the information entropy method is employed to determine their weight and the comprehensive evaluation results, and these results are analyzed according to SPC. Finally, a numerical example is used to demonstrate the feasibility of the proposed method. The major contribution of this paper is the combination of SQLIQ and JIT philosophy, while an objective and comprehensive evaluation method of SCLIQ from the JIT perspective is developed. The results are useful for evaluating SCLIQ and determining the best direction of improvement activities. INDEX TERMS supply chain; logistics; information quality; Just-In-Time; statistical process control method (SPC); information entropy method

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Section: F Comprehensive Evaluationmentioning

confidence: 99%

Section: Comprehensive Evaluationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Supply Chain Logistics Information Quality Evaluation From Just-in-Time Perspective

et al. 2020

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“…Statics show that automotive systems in manufacturing processes can recover vast costs to the companies. 18 This briefly can be achieved by improving the combination of assembly technology and system.…”

Section: Architecture Of Agent Based Control Systemmentioning

confidence: 99%

Applications of control engineering in industry 4.0: utilizing internet of things to design an agent based control architecture for smart material handling system

Azizi

Yazdi

Humairi³

et al. 2018

IRATJ

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The influence of global economy has led to changes in the conventional approaches for manufacturing companies. In this case, manufacturing companies has taken under consideration several essential characteristics such as real-time reaction to changes, quick and quality response in satisfying customer requests, in both hardware equipment and software modules by which the production processes are improved for next generation manufacturing systems. Nowadays, material handling system for manufacturing purposes is the key component for any modern manufacturing processes. Additionally, due to high variety of products and shorter response times in today's manufacturing industry, the demand for smart material handling system has increased. Therefore, to recover these demands, custom-built systems have to be implemented which requires individually created control software which deals with flow control, product routings, layout and products distribution. Internet of Things (IoT) is a concept that is set to enhance manufacturing by improving output quality and workflow efficiency. Nowadays manufacturing industries are utilizing internet of things concept as a network that connects multiple sensors and devices through the internet. There are thousands of these sensors within a manufacturing environment, from the temperature gauges to the individual components on the material handling system, connecting data from these devices can improve business efficiency, innovation as well as strengthening security. However; if the data is not connected to a single common platform talking the same language, these potential gains are lost. The aim of this research is to develop an agent based feedback control system and implement it utilizing IoT to control the material handling system in manufacturing industry.

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“…En lo que respecta al análisis de modelado y simulación de sistemas kanban utilizando la metodología de Dinámica de Sistemas (DS) se han desarrollado interesantes trabajos en aplicaciones prácticas y planteamientos teóricos [5,6].…”

Section: Introductionunclassified

Modelo dinámico de las afectaciones del tiempo de ciclo kanban en el flujo de producción de una línea de ensamble

Alvarado¹,

Quijada²,

López³

2016

RCS

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Resumen. En este artículo se presenta el modelo dinámico del proceso de ensamble de reductores de velocidad como parte de una actividad realizada en un taller de simulación kanban dirigido a alumnos de ingeniería industrial. El principal objetivo del modelo desarrollado es analizar el comportamiento de los niveles de inventario de las estaciones de trabajo y las acumulaciones de las tarjetas kanban (ordenes de producción) derivado de las afectaciones del tiempo de ciclo kanban en los flujos de producción. Los resultados del análisis y evaluación muestran que, cuando el tiempo de ciclo kanban es superior al tiempo de entrega del lote de producción entre estaciones, se genera una acumulación de órdenes de producción. Esto ocasiona que una vez que el flujo de producción alcanza su máximo rendimiento este disminuya. Esa situación provoca que los niveles de inventario en proceso no correspondan al ritmo del cliente, generando órdenes de producción sin entregar a tiempo.Palabras claves: Dinámica de sistemas, flujo de producción, sistema kanban.

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Effective Material Handling System for JIT Automotive Production Line

Cited by 14 publications

References 2 publications

Supply Chain Logistics Information Quality Evaluation From Just-in-Time Perspective

Supply Chain Logistics Information Quality Evaluation From Just-in-Time Perspective

Applications of control engineering in industry 4.0: utilizing internet of things to design an agent based control architecture for smart material handling system

Modelo dinámico de las afectaciones del tiempo de ciclo kanban en el flujo de producción de una línea de ensamble

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