Flexible job shop with continuous material flow

Bożek, Andrzej; Wysocki, Marian

doi:10.1080/00207543.2014.955925

Cited by 19 publications

(9 citation statements)

References 27 publications

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“…minimisation of maximal lateness) and an equal machine utilisation over time. Bożek and Wysocki (2015) analysed continuous flow flexible job shop (CF-FJS) problem that combines the flexible job shop (FJS) problem and a dedicated continuous material flow model (MFM). In this study, the operations are represented by material flow functions derived by integration of arbitrarily defined speed patterns.…”

Section: Literature Reviewmentioning

confidence: 99%

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A dynamic model and an algorithm for short-term supply chain scheduling in the smart factory industry 4.0

Ivanov

Dolgui

Sokolov

et al. 2015

International Journal of Production Research

460

194

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International audienceSmart factories Industry 4.0 on the basis of collaborative cyber-physical systems represents a future form of industrial networks. Supply chains in such networks have dynamic structures which evolve over time. In these settings, short-term supply chain scheduling in smart factories Industry 4.0 is challenged by temporal machine structures, different processing speed at parallel machines and dynamic job arrivals. In this study, for the first time, a dynamic model and algorithm for short-term supply chain scheduling in smart factories Industry 4.0 is presented. The peculiarity of the considered problem is the simultaneous consideration of both machine structure selection and job assignments. The scheduling approach is based on a dynamic non-stationary interpretation of the execution of the jobs and a temporal decomposition of the scheduling problem. The algorithmic realisation is based on a modified form of the continuous maximum principle blended with mathematical optimisation. A detailed theoretical analysis of the temporal decomposition and computational complexity is performed. The optimality conditions as well as the structural properties of the model and the algorithm are investigated. Advantages and limitations of the proposed approach are discussed

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Section: Literature Reviewmentioning

confidence: 99%

“…Examples of such problems can be found in the studies by Kyparisis and Koulamas (2006) and Tahar et al (2006) and Bożek and Wysocki (2015). The peculiarity of the problem under consideration is the simultaneous consideration of both machine structure selection, continuous flows, and job assignment.…”

Section: Introductionmentioning

confidence: 97%

A dynamic model and an algorithm for short-term supply chain scheduling in the smart factory industry 4.0

Ivanov

Dolgui

Sokolov

et al. 2015

International Journal of Production Research

460

194

View full text Add to dashboard Cite

show abstract

“…These systems are the MSS and constitute a variant of Business Information tools, i.e. information systems supporting business functions, such as those provided by the SIEMENS PREACTOR business unit or SAP's integrated management systems (Bożek and Wysocki 2015). Framinan and Ruiz (2010) The system is constituted by the following components: a Database Management module, an Automatic Schedule Generator, a Schedule Editor and a Performance Evaluator.…”

Section: Manufacturing Scheduling Systemsmentioning

confidence: 99%

Industry 4.0: Smart Scheduling

Rossit

Tohmé

Frutos

2018

International Journal of Production Research

237

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Smart Manufacturing and Industry 4.0 production environments integrate the physical and decisional aspects of manufacturing processes into autonomous and decentralised systems. One of the main aspects in these systems is production planning, in particular scheduling operations on machines. We introduce here a new decision-making schema, Smart Scheduling, intended to yield flexible and efficient production schedules on the fly, taking advantage of the features of these new environments. The ability to face unforeseen and disruptive events is one of the main improvements in our proposed schema, which uses an efficient screening procedure (Tolerance Scheduling) to lessen the need of rescheduling in the face of those events.

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“…Demir and Işleyen 2014), others are based on hybrid methods combining FJS problem and a dedicated continuous material flow model (Bozek and Wysocki 2015) or as a combination of group constraint with flexible flow shop to minimize makespan (Kurz and Askin 2004;Logendran et al 2005). In some other cases authors studied a hybrid flow shop scheduling problem with assembly operations at stage two (Fattahi et al 2014;Yokoyama 2004;Riane et al 2002;Wang and Liu 2013).…”

Section: Literature Reviewmentioning

confidence: 99%

Dispatching algorithm for production programming of flexible job-shop systems in the smart factory industry

et al. 2017

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In today highly competitive and globalized markets, an efficient use of production resources is necessary for manufacturing enterprises. In this research, the problem of scheduling and sequencing of manufacturing system is presented. A flexible job shop problem sequencing problem is analyzed in detail. After formulating this problem mathematically, a new model is proposed. This problem is not only theoretically interesting, but also practically relevant. An illustrative example is also conducted to demonstrate the applicability of the proposed model

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Flexible job shop with continuous material flow

Abstract: This document describes the material flow model (MFM) in details. It presents mathematical basics of the formalism and introduces its properties. A short implementation note is also given.

Cited by 19 publications

References 27 publications

A dynamic model and an algorithm for short-term supply chain scheduling in the smart factory industry 4.0

A dynamic model and an algorithm for short-term supply chain scheduling in the smart factory industry 4.0

Industry 4.0: Smart Scheduling

Dispatching algorithm for production programming of flexible job-shop systems in the smart factory industry

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