Production rescheduling review: Opportunities for industrial integration and practical applications

Uhlmann, Iracyanne Retto; Frazzon, Enzo Morosini

doi:10.1016/j.jmsy.2018.10.004

Cited by 74 publications

(18 citation statements)

References 59 publications

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“…Propõe-se a utilização dos conceitos da Indústria 4.0 para que as organizações tenham flexibilização e conectividade dos processos, proporcionando um planejamento operacional mais adequado à realidade, visto também que as informações estão dispostas em tempo real [12]. Em [13], projeta-se como um aspecto importante neste novo contexto industrial, a obtenção das integrações horizontal, vertical e a digital em toda a planta.…”

Section: A Indústria 40unclassified

“…Verifica-se em [1] que a instabilidade e a volatilidade dos mercados exigem das organizações um constante exercício de adaptabilidade, onde frequentemente é necessário inovar e tratar os problemas a partir de novas metodologias. Já em [13] confere-se que a transição para o contexto da Indústria 4.0 exige a superação de obstáculos e de persistência para manter o foco na realização das ações pertinentes. Fatores como descentralização, adaptabilidade, flexibilidade e integração das informações devem estar presentes nessa trajetória.…”

Section: A Indústria 40unclassified

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Aplicação de um algoritmo evolutivo na solução de problemas de sequenciamento da produção

Schneider

Corso

2020

SCI

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Section: A Indústria 40unclassified

Aplicação de um algoritmo evolutivo na solução de problemas de sequenciamento da produção

Schneider

Corso

2020

SCI

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“…Different scheduling and rescheduling models have been developed to improve the reliability and efficiency of production systems. However, most existing models work only under ideal conditions, since they do not consider external events (Uhlmann and Frazzon, 2018). Indeed, various unpredictable events could occur at the shop-floor level and introduce inconsistencies into the ongoing schedule.…”

Section: Introductionmentioning

confidence: 99%

“…Indeed, various unpredictable events could occur at the shop-floor level and introduce inconsistencies into the ongoing schedule. Therefore, it is important to broaden the research area by analysing existing rescheduling models and creating new ones to mitigate the consequences of unpredictable events (Uhlmann and Frazzon, 2018).…”

Section: Introductionmentioning

confidence: 99%

A Generic Methodology for Calculating Rescheduling Time for Multiple Unexpected Events in the Era of Zero Defect Manufacturing

et al. 2021

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Nowadays, the manufacturing industry is constantly changing. Production systems must operate in a highly dynamic environment where unexpected events could occur and create disruption, making rescheduling inevitable for manufacturing companies. Rescheduling models are fundamental to the robustness of production processes. This paper proposes a model to address rescheduling caused by unexpected events, aiming to achieve the zero-defect manufacturing (ZDM) concept. The goal of the model is to incorporate traditional and ZDM–oriented events into one methodology to calculate when the next rescheduling will be performed to effectively react to unexpected events. The methodology relies on the definition of two key time parameters for each event type: event response time (RT) and event delay response time (DRT). Based on these parameters, an event management algorithm is designed to identify the optimal rescheduling solution. The DRT parameter is calculated based on a multi-parametric dynamic formula to capture the dynamics of production. Moreover, ANOM, and ANOVA methods are used to analyse the behaviour of the developed method and to assess the level of robustness of the proposed approach. Finally, a case study based on real production scenarios is conducted, a series of simulation experiments are performed, and comparisons with other rescheduling policies are presented. The results demonstrate the effectiveness of the proposed event management algorithm for managing rescheduling.

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“…This allows for a rolling horizon application of the developed algorithm. As pointed out by Uhlmann and Frazzon [4], more contributions are still needed for the dynamic rescheduling problems since they represent an important part of the integration of the fourth industrial revolution.…”

Section: Introductionmentioning

confidence: 99%

Bi-Objective Dynamic Multiprocessor Open Shop Scheduling: An Exact Algorithm

Abdelmaguid

2020

Algorithms

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An important element in the integration of the fourth industrial revolution is the development of efficient algorithms to deal with dynamic scheduling problems. In dynamic scheduling, jobs can be admitted during the execution of a given schedule, which necessitates appropriately planned rescheduling decisions for maintaining a high level of performance. In this paper, a dynamic case of the multiprocessor open shop scheduling problem is addressed. This problem appears in different contexts, particularly those involving diagnostic operations in maintenance and health care industries. Two objectives are considered simultaneously—the minimization of the makespan and the minimization of the mean weighted flow time. The former objective aims to sustain efficient utilization of the available resources, while the latter objective helps in maintaining a high customer satisfaction level. An exact algorithm is presented for generating optimal Pareto front solutions. Despite the fact that the studied problem is NP-hard for both objectives, the presented algorithm can be used to solve small instances. This is demonstrated through computational experiments on a testbed of 30 randomly generated instances. The presented algorithm can also be used to generate approximate Pareto front solutions in case computational time needed to find proven optimal solutions for generated sub-problems is found to be excessive. Furthermore, computational results are used to investigate the characteristics of the optimal Pareto front of the studied problem. Accordingly, some insights for future metaheuristic developments are drawn.

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Production rescheduling review: Opportunities for industrial integration and practical applications

Cited by 74 publications

References 59 publications

Aplicação de um algoritmo evolutivo na solução de problemas de sequenciamento da produção

Aplicação de um algoritmo evolutivo na solução de problemas de sequenciamento da produção

A Generic Methodology for Calculating Rescheduling Time for Multiple Unexpected Events in the Era of Zero Defect Manufacturing

Bi-Objective Dynamic Multiprocessor Open Shop Scheduling: An Exact Algorithm

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