Lead time and response time in a pull production control system |
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| Institution: | 1. Krannert Graduate School of Management, Purdue University, West Lafayette, IN 47907, USA;2. Anderson Graduate School of Management, UCLA, Los Angeles, CA 90095, USA;1. Department of Cardiac Surgery, Innsbruck Medical University, Innsbruck, Austria;2. Department of Cardiology, Innsbruck Medical University, Innsbruck, Austria;3. Department of Medical Statistics, Informatics and Health Economics, Innsbruck Medical University, Innsbruck, Austria;4. Department of Anaesthesiology and Intensive Care Medicine, Innsbruck Medical University, Innsbruck, Austria;1. Servicio de Cardiología, Hospital de Manacor, Manacor, Baleares, España;2. Servicio de Cardiología, Hospital General Universitario Gregorio Marañón, CIBER de Enfermedades Cardiovasculares (CIBERCV), Instituto de Investigación Sanitaria Gregorio Marañón, Madrid, España;3. Universidad Complutense y Universidad Europea, Madrid, España;4. Servicio de Cardiología, Instituto Cardiovascular, Hospital Clínico San Carlos, Madrid, España;5. Servicio de Cardiología, Hospital Universitario Vall d’Hebron, Barcelona, España;6. Unidad de Cuidados Intensivos Cardiológicos, Servicio de Cardiología, Hospital de Sant Pau, Instituto de Investigación Biomédica Sant Pau (IIB Sant Pau), Barcelona, España;7. Servicio de Cardiología, Hospital Virgen de la Macarena, Sevilla, España;8. Servicio de Cardiología, Hospital Universitario de Salamanca, Instituto de Investigacion Biomédica de Salamanca (IBSAL), CIBER de Enfermedades Cardiovasculares (CIBERCV), Salamanca, España;9. Servicio de Cardiología, Hospital de La Princesa, Madrid, España;10. Servicio de Cardiología, Hospital Universitario Arnau de Vilanova, Lérida, España;11. Servicio de Cardiología, Hospital Clínico Lozano Blesa, Zaragoza, España;1. Development of Mechanical and Automotive Engineering, Jeonju University, Jeonju 55069, Republic of Korea;2. CF Technical Division, AUK Corporation, Iksan 54630, Republic of Korea;1. Oil Company RussNeft, 69, Pyatnitskaya st., Moscow, Russia;2. National Research University Higher School of Economics, Russian Federation;3. Lomonosov Moscow State University, Russia;4. National Research Nuclear University “MEPhI” (Moscow Engineering Physics Institute), 31, Kashirskoe Highway, Moscow, Russia;5. International Centre for Nuclear Safety, Minatom of Russia, 2/8, Krasnoselskaya M. Street, Moscow, Russia;6. Corporate Finance Department, Summa Group, Russia;1. School of Management Science and Engineering, Dalian University of Technology, Dalian 116023, China;2. Faculty of Science, Kunming University of Science and Technology, Kunming 650093, China;3. College of Information Science and Engineering, Northeastern University, Shenyang 110819, China;4. Department of Healthcare Management, Yuanpei University, Hsinchu, Taiwan;5. Graduate Institute of Business Administration, Cheng Shiu University, Kaohsiung, Taiwan;6. Department of Statistics, Feng Chia University, Taichung, Taiwan |
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| Abstract: | In the late 80s, most manufacturers have shifted their manufacturing strategies from cost and quality to speed. This paper focuses on two performance measures of speed: manufacturing lead time and response time. Manufacturing lead time is the sum of the processing time to convert raw material to finished goods and the waiting time at the buffers. Response time is the time between the customer places an order and the customer receives the order. In this paper we develop a queueing model of a pull-based production control system for a single-stage facility. The intent of the model is two-fold. First, we highlight the trade-off between manufacturing lead time and response time. Second, we develop an optimization model to determine an optimal control system that guarantees certain delivery performance (in terms of response time). |
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