Integrative process plan model and representation for intelligent distributed manufacturing planning

Šormaz, Dušan; Arumugam, Jaikumar; Rajaraman, Srinivas

doi:10.1080/00207540410001696320

Cited by 29 publications

(8 citation statements)

References 13 publications

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“…The IMPlanner CAPP tool is an ongoing software project under development at Ohio University [11] that aims to allow the end user to generate alternate, precise and detailed manufacturing process selection, sequencing and scheduling plans, using CAD design files as a starting point. This is achieved due to the different modules encoded in the IMPlanner software than can convert design features into manufacturing steps and attribute them to specific manufacturing process.…”

Section: Implanner Softwarementioning

confidence: 99%

RULE BASED PROCESS SELECTION OF MILLING PROCESSES BASED ON GD&T REQUIREMENTS

Šormaz¹,

Gouveia²,

Sarkar³

2018

J. Prod. Eng.

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The IMPlanner is an ongoing CAPP software project that enables rapid and detailed process selection of manufacturing processes based on specific details of CAD models such as GD&T requirements and feature recognition. A mapping of the different manufacturing routes possible for a given CAD design are outputted by the software, electing the optimal solution. Previously this software focused mainly on hole making operations however, further research has enabled its expansion towards milling operations.

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Section: Implanner Softwarementioning

confidence: 99%

RULE BASED PROCESS SELECTION OF MILLING PROCESSES BASED ON GD&T REQUIREMENTS

Šormaz¹,

Gouveia²,

Sarkar³

2018

J. Prod. Eng.

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“…In the knowledge based system more than 50 prototypes are developed [2]. Some of the recent reports presents new approaches in CAPP like virtual manufacturing [3], distributed process planning [4], CAPP as integration tool [5].…”

Section: Previous Workmentioning

confidence: 99%

“…This section starts with an explanation of the IMPlanner system, an existing CAPP system which has been under development at Ohio University [11]. IMPlanner system has been developed using object oriented approach.…”

Section: Implanner Systemmentioning

confidence: 99%

RULE-BASED PROCESS PLANNING AND SETUP PLANNING WITH CONSIDERATIONS OF GD&T REQUIREMENTS

Šormaz

Wakhare

Arafat

2017

IJAQ

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“…Palmer defined conventional scheduling as a task that uses input from rigid process plans [4] . These plans specify a unique choice of machines for each operation, and a unique sequence of operations.…”

Section: Integrated Process Planning and Schedulingmentioning

confidence: 99%

Integration of process planning and production scheduling with particle swarm optimization (PSO) algorithm and fuzzy inference systems

et al. 2005

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Integration of process planning with scheduling by considering the manufacturing system's capacity, cost and capacity in its workshop is a critical issue. The concurrency between them can also eliminate the redundant process and optimize the entire production cycle, but most integrated process planning and scheduling methods only consider the time aspects of the alternative machines when constructing schedules. In this paper, a fuzzy inference system (FIS) in choosing alternative machines for integrated process planning and scheduling of a job shop manufacturing system is presented. Instead of choosing alternative machines randomly, machines are being selected based on the machines reliability. The mean time to failure (MTF) values is input in a fuzzy inference mechanism, which outputs the machine reliability. The machine is then being penalized based on the fuzzy output. The most reliable machine will have the higher priority to be chosen. In order to overcome the problem of un-utilization machines, sometimes faced by unreliable machine, the particle swarm optimization (PSO) have been used to balance the load for all the machines. Simulation study shows that the system can be used as an alternative way of choosing machines in integrated process planning and scheduling.

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Integrative process plan model and representation for intelligent distributed manufacturing planning

Cited by 29 publications

References 13 publications

RULE BASED PROCESS SELECTION OF MILLING PROCESSES BASED ON GD&T REQUIREMENTS

RULE BASED PROCESS SELECTION OF MILLING PROCESSES BASED ON GD&T REQUIREMENTS

RULE-BASED PROCESS PLANNING AND SETUP PLANNING WITH CONSIDERATIONS OF GD&T REQUIREMENTS

Integration of process planning and production scheduling with particle swarm optimization (PSO) algorithm and fuzzy inference systems

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