PROPLAN: an expert system for optimal planning of sheet metal operations

Singh, Rajender; Sekhon, G.S.

doi:10.1016/j.jmatprotec.2004.08.023

Cited by 13 publications

(5 citation statements)

References 6 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…knowledge-based systems have been used to solve various problems in manufacturing systems, including various design problems (Basu et al 1995), planning (Singh and Sekhon 2005), machine monitoring, diagnosis and maintenance (Majstorovic and Milacic 1990), system configuration, managing complexity and uncertainty (Monostroni 2003), process control and monitoring (Barschdorff et al 1997;Lekova and Batanov 1998), quality assurance (Sibalija 1992;Smith and Dagli 1994;Westkamper 1997;El-Shal and Morris 2000) etc. Since 1980s, ES and ES-related types of IS i.e.…”

Section: Multiresponse Optimisation Using Expert Systemmentioning

confidence: 99%

Advanced Multiresponse Process Optimisation

Šibalija¹,

Majstorovic²

2016

View full text Add to dashboard Cite

Section: Multiresponse Optimisation Using Expert Systemmentioning

confidence: 99%

Advanced Multiresponse Process Optimisation

Šibalija¹,

Majstorovic²

2016

View full text Add to dashboard Cite

“…Since 1980s, ES and ES-related types of IS i.e. knowledge-based systems have been used to solve various problems in manufacturing systems, including various design problems (Basu et al 1995), planning (Singh and Sekhon 2005), machine monitoring, diagnosis and maintenance (Majstorovic and Milacic 1990), system configuration, managing complexity and uncertainty (Monostroni 2003), process control and monitoring (Barschdorff et al 1997;Lekova and Batanov 1998), quality assurance (Sibalija 1992;Smith and Dagli 1994;Westkamper 1997;El-Shal and Morris 2000) etc.…”

Section: Multiresponse Optimisation Using Expert Systemmentioning

confidence: 99%

Review of Multiresponse Process Optimisation Methods

Šibalija

Majstorovic

2015

Advanced Multiresponse Process Optimisation

View full text Add to dashboard Cite

The review of methods used for multiresponse process parameter design and similar multiobjective optimisation problems is discussed in this chapter, implying the following classification: (1) conventional methods based on statistical or mathematical techniques: (i) experimental design techniques (response surface methodology, Taguchi's robust parameter design and related approaches), and (ii) iterative mathematical search techniques; (2) non-conventional methods based on artificial intelligence techniques: (i) fuzzy logic, (ii) artificial neural networks, (iii) metaheuristic search techniques (genetic algorithm, simulated annealing, particle swarm optimisation, ant colony optimisation, tabu search, and recent evolutionary algorithms such as artificial bee colony algorithm, biogeography-based optimisation, and teaching-learning-based optimisation), and (iv) expert systems.

show abstract

“…A list of chief data sources utilized during the present investigation can be found in [11]. Information on die-set selection was obtained from industrial experts by holding discussions on typical problems and letting the experts talk about the approach, formulae and thumb-rules relied upon by them.…”

Section: Acquisition Of Information On Die-set Selectionmentioning

confidence: 99%