Application of Dynamic Programming to Optimize Tool Replacement Schedules for Multi-Tool Operations Involving Distributed Tool Lives

Bao, Ho Tu

doi:10.1115/1.3254767

Cited by 6 publications

(6 citation statements)

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“…However, studies adopting a more unified approach towards all aspects of tool management have recently started appearing in the literature. Stecke (1983Stecke ( , 1989; Stecke and Talbot (1985); Kusiak (1986a); Sarin and Chen (1987);Cuppan (1986); Ventura et al (1988) Bao (1980Kordysh (1987); Sharit andElhence (1989) Crite et al (1985); Maccarini et al (1987); Perera and Carrie (1987);Hedlund et al (1990) Rutelli andCuppini (1988); Kincaid (1989);Powell et al (1984); Gee et al (1984);Brown (1988); Stockline (1984 and) Knutton (1990);Quinlan (1988b); Kochan (1986); Murphy and Kay (1987); Ames (1986);Brigida (1986) Brunette (1989; Bellmann and Becker (1989) Mason (1986Gayman (1987) …”

Section: Tool Management Researchmentioning

confidence: 99%

“…Bao (1980) has developed a dynamic programming formulation to optimize tool replacement schedules under a specified set of machining parameters. In his formulation, four options for tool replacement are considered at each stage: (1) replace no tools, (2) replace a particular tool, (3) replace a group of tools, and (4) replace all tools.…”

Section: Tool Replenishmentmentioning

confidence: 99%

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Cutting-tool management in computer-integrated manufacturing

Veeramani

Upton

Barash

1992

Int J Flex Manuf Syst

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Abstract. The problem of cutting tool management has been brought to the forefront with the emergence of computerintegrated manufacturing (CIM) and, in particular, flexible manufacturing systems (FMSs). The financial and operational ramifications of effective tool management has spurred considerable research in this area during the past decade and many researchers are proposing sound solutions to various facets of this broad-ranging and difficult problem. This paper identifies critical areas of research for the development of tool management systems in CIM. To develop a framework for this, the paper examines and categorizes work in academia and in industry on the management of cutting-tools in CIM and describes some key implementations, particularly in the metalcutting industry. The solution of manufacturing problems generally demands an eclectic approach, and for this reason, we have tried to taxonomize, describe, and critique the various research thrusts in an attempt to provide a synthesis of use in more unified approaches.

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Section: Tool Management Researchmentioning

confidence: 99%

Section: Tool Replenishmentmentioning

confidence: 99%

Cutting-tool management in computer-integrated manufacturing

Veeramani

Upton

Barash

1992

Int J Flex Manuf Syst

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“…A thorough review of the solution methodologies related to tool replacement can be found in McCullough [5], Armarego and Brown [6], Pa'sko [7], Batra and Barash [8], Bao [9], LaCommare et al [10], Sharit and Elhence [11], Zhou et al [12] and Tak [13]. As has been mentioned by Zhou et al [12], the various authors have classified tool replacement strategies in different ways.…”

Section: Studies On Tool Replacementmentioning

confidence: 99%

“…A complete Tool Replacement Strategy specifies a tool change schedule based upon the economic service lives of tools and a control policy regarding unscheduled tool changes following breakage. The most realistic replacement strategies have considered the distributed nature of tool lives under actual machining parameters, as well as the option to change several tools once one fails [9,10], rather than considering only expected lives and single tool replacement [5,6]. All of these tool replacement studies have considered one machine in isolation.…”

Section: Studies On Tool Replacementmentioning

confidence: 99%

Intelligent Tool Management Strategies for Automated Manufacturing Systems

Rao¹,

Patvardhan²,

Singh³

2011

ICA

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With the increase in automation and use of computer control in machine tools, the number of cutting tools per machining setup is on the increase. On one hand, such multi-tool setups offer the advantages of reduced down-time and cost of production and require less space and in-process inventory, and on the other hand, require proper tool management for economic operations. A number of strategies have been devised to solve the tool selection problems and a number of tool replacement policies have been proposed in the past. These strategies have been solved in isolation, whereas, a comprehensive algorithm for proper selection of tools out of those available in the tool magazine for performing operation and for replacement of tools on failure/wear is necessary. In this paper, taking cue from the computer memory management policies, four tool selection strategies have been presented and their performance in tandem with various tool replacement policies has been studied. The effect of important parameters such as reduction of tool life due to regrinding, limited number of regrindings, catastrophic failures etc. have been considered. Cost has been computed for each combination of tool selection and replacement policy. Also, the number of machine stoppages has been worked out in each case. The results indicate that the combination of various selection strategies with suitable replacement policies affects the overall cost

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“…Bao [18] proposed a dynamic programming model for a tool replacement policy in a multi-tool environment. The author used log-normal, Weibull, and gamma probability functions to represent actual tool life distributions.…”

Section: Tool Life Distributionsmentioning

confidence: 99%

The Impact of Stochastic Tool Life on Shop Performance: A Simulation Study

2000

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Much of the research in tool management has ignored the potential impact of tool life on shop performance. Tool management research has typically assumed that tool life is deterministic and can be predicted accurately. Since tool life is a function of its quality, cutting speed, depth and other environmental factors, no two identi cal tools exhibit the exact same tool life. An as sumption of stochastic tool life is more realistic on the actual shop floor. In this paper, we have developed a simulation model to examine the effects of stochastic tool life, dispatching rules and tool failure penalties on shop performance.

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Application of Dynamic Programming to Optimize Tool Replacement Schedules for Multi-Tool Operations Involving Distributed Tool Lives

Cited by 6 publications

References 0 publications

Cutting-tool management in computer-integrated manufacturing

Cutting-tool management in computer-integrated manufacturing

Intelligent Tool Management Strategies for Automated Manufacturing Systems

The Impact of Stochastic Tool Life on Shop Performance: A Simulation Study

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