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MEASURING THE EFFECT OF ERRATIC DEMANDON SIMULATED MULTI-CHANNEL MANUFACTURINGSYSTEM PERFORMANCE

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Date Issued:
2004
Abstract/Description:
ABSTRACT To handle uncertainties and variabilities in production demands, many manufacturing companies have adopted different strategies, such as varying quoted lead time, rejecting orders, increasing stock or inventory levels, and implementing volume flexibility. Make-to-stock (MTS) systems are designed to offer zero lead time by providing an inventory buffer for the organizations, but they are costly and involve risks such as obsolescence and wasted expenditures. The main concern of make-to-order (MTO) systems is eliminating inventories and reducing the non-value-added processes and wastes; however, these systems are based on the assumption that the manufacturing environments and customers' demand are deterministic. Research shows that in MTO systems variability and uncertainty in the demand levels causes instability in the production flow, resulting in congestion in the production flow, long lead times, and low throughput. Neither strategy is wholly satisfactory. A new alternative approach, multi-channel manufacturing (MCM) systems are designed to manage uncertainties and variabilities in demands by first focusing on customers' response time. The products are divided into different product families, each with its own manufacturing stream or sub-factory. MCM also allocates the production capacity needed in each sub-factory to produce each product family. In this research, the performance of an MCM system is studied by implementing MCM in a real case scenario from textile industry modeled via discrete event simulation. MTS and MTO systems are implemented for the same case scenario and the results are studied and compared. The variables of interest for this research are the throughput of products, the level of on-time deliveries, and the inventory level. The results conducted from the simulation experiments favor the simulated MCM system for all mentioned criteria. Further research activities, such as applying MCM to different manufacturing contexts, is highly recommended.
Title: MEASURING THE EFFECT OF ERRATIC DEMANDON SIMULATED MULTI-CHANNEL MANUFACTURINGSYSTEM PERFORMANCE.
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Name(s): Kohan, Nancy, Author
Kulonda, Dennis, Committee Chair
University of Central Florida, Degree Grantor
Type of Resource: text
Date Issued: 2004
Publisher: University of Central Florida
Language(s): English
Abstract/Description: ABSTRACT To handle uncertainties and variabilities in production demands, many manufacturing companies have adopted different strategies, such as varying quoted lead time, rejecting orders, increasing stock or inventory levels, and implementing volume flexibility. Make-to-stock (MTS) systems are designed to offer zero lead time by providing an inventory buffer for the organizations, but they are costly and involve risks such as obsolescence and wasted expenditures. The main concern of make-to-order (MTO) systems is eliminating inventories and reducing the non-value-added processes and wastes; however, these systems are based on the assumption that the manufacturing environments and customers' demand are deterministic. Research shows that in MTO systems variability and uncertainty in the demand levels causes instability in the production flow, resulting in congestion in the production flow, long lead times, and low throughput. Neither strategy is wholly satisfactory. A new alternative approach, multi-channel manufacturing (MCM) systems are designed to manage uncertainties and variabilities in demands by first focusing on customers' response time. The products are divided into different product families, each with its own manufacturing stream or sub-factory. MCM also allocates the production capacity needed in each sub-factory to produce each product family. In this research, the performance of an MCM system is studied by implementing MCM in a real case scenario from textile industry modeled via discrete event simulation. MTS and MTO systems are implemented for the same case scenario and the results are studied and compared. The variables of interest for this research are the throughput of products, the level of on-time deliveries, and the inventory level. The results conducted from the simulation experiments favor the simulated MCM system for all mentioned criteria. Further research activities, such as applying MCM to different manufacturing contexts, is highly recommended.
Identifier: CFE0000240 (IID), ucf:46275 (fedora)
Note(s): 2004-12-01
M.S.M.E.
Engineering and Computer Science, Department of Industrial Engineering and Management Systems
Masters
This record was generated from author submitted information.
Subject(s): Inventory level
lead time
throughput of products
simulation
Arena
erratic demand
variable and uncertain demand
stochastic demand
dynamic demand
demand forecast
Multi-channel Manufacturing
Quick response
Lean manufacturing
Just in time
production planning
volume flexibility
uni-directional production flow
manufacturing methodologies.
Persistent Link to This Record: http://purl.flvc.org/ucf/fd/CFE0000240
Restrictions on Access: public
Host Institution: UCF

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