Generic machining process sequencing through a revised enriched machining feature concept

Givehchi, Mohammad; Haghighi, Azadeh; Wang, Lihui

doi:10.1016/j.jmsy.2015.04.004

Cited by 49 publications

(12 citation statements)

References 34 publications

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“…Another major issue in the adoption of Industry 4.0 standards is productivity. Givehchi [19] sought to improve efficiency by sequencing machining tasks in a more efficient manner. Dombrowski and Ernst [20] simulated various growth scenarios at the enterprise-level with the aim of reconfiguring production lines to improve production flows.…”

Section: Related Workmentioning

confidence: 99%

A Low-Cost Add-On Sensor and Algorithm to Help Small- and Medium-Sized Enterprises Monitor Machinery and Schedule Processes

et al. 2019

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Since the concept of Industry 4.0 emerged, an increasing number of major manufacturers have incorporated relevant technologies to monitor machinery and schedule processes so as to increase yield and optimize production. However, most machinery monitoring technologies are far too expensive for small- and medium-sized enterprises. Furthermore, the production processes at small- and medium-sized enterprises are simpler and can thus be optimized without excessively complex scheduling systems. This study therefore proposed the use of cheaper add-on sensors for monitoring machinery and integrated them with an algorithm that can more swiftly produce results that meet multiple objectives. The proposed algorithm is meant to extend the capabilities of small- and medium-sized enterprises in monitoring machinery and scheduling processes, thereby enabling them to contend on an equal footing with larger competitors. Finally, we performed an experiment at an actual spring enterprise to demonstrate the validity of the proposed algorithm.

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Section: Related Workmentioning

confidence: 99%

A Low-Cost Add-On Sensor and Algorithm to Help Small- and Medium-Sized Enterprises Monitor Machinery and Schedule Processes

et al. 2019

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“…The process elements determined by MPP include machining processes, operations, resources and relevant parameters. Many technologies from the domain of computer science have been used to automate the activities in MPP, including: (1) Feature-based technologies (Givehchi, Haghighi, & Wang, 2015); (2) Knowledge-based technologies (Denkena, Shpitalni, Kowalski, Molcho, & Zipori, 2007); (3) Artificial-intelligent-based technologies (Quintanilla, Cardin, L'Anton, & Castagna, 2016); (4) Standard-compliant technologies (Xu, Klemm, Proctor, & Suh, 2006); and (5) Internet-based technologies (Wang, 2013).…”

Section: Machining Process Planning For Part Varietymentioning

confidence: 99%

Reconfigurable machining process planning for part variety in new manufacturing paradigms: Definitions, models and framework

Xia

Etienne

Dantan

et al. 2018

Computers & Industrial Engineering

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Conventional machining process planning approaches are inefficient to handle the process planning complexity induced by part variety. Reconfigurable process planning is a new process planning approach which has been well recognized as a key enabler for current manufacturing paradigms. However, in the literature, there is neither a comprehensive part variety representation model to support reconfigurable process planning nor a global solution framework to instruct the generation of the feasible process plans for a specific part variant. Therefore, this paper extends the concept of reconfigurable process planning to a concept of reconfigurable machining process planning which targets the process plan generation for a part family. A solution framework is developed for reconfigurable machining process planning. In this framework, a feature-based part variety model is proposed to represent a part family; A reconfigurable machining process plan is defined as a set of modular components which can be configured/reconfigured into the machining process plans for any part variant in the family; a novel configuration approach is proposed to generate the process plan components for a specific part variant while configuring this part variant from the family. The feasibility and effectiveness of the proposed framework and models are tested in a real case study.

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“…To validate and evaluate the proposed production system based on Cloud, ICMS is implemented based on previous research works [28,29,30]. In the Cloud that hosts virtual environments and service modules.…”

Section: Implementations and Case Studymentioning

confidence: 99%

ICMS: A Cloud-Based System for Production Management

Wang

Givehchi

2015

Advances in Production Management Systems: Innovative Production Management Towards Sustainable Growth

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Generic machining process sequencing through a revised enriched machining feature concept

Cited by 49 publications

References 34 publications

A Low-Cost Add-On Sensor and Algorithm to Help Small- and Medium-Sized Enterprises Monitor Machinery and Schedule Processes

A Low-Cost Add-On Sensor and Algorithm to Help Small- and Medium-Sized Enterprises Monitor Machinery and Schedule Processes

Reconfigurable machining process planning for part variety in new manufacturing paradigms: Definitions, models and framework

ICMS: A Cloud-Based System for Production Management

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