A classification and review of timed Markov models of manufacturing systems

Papadopoulos, Chrissoleon T.; Li, Jingshan; O’Kelly, M.E.J.

doi:10.1016/j.cie.2018.12.019

Cited by 85 publications

(32 citation statements)

References 475 publications

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“…Different approaches have been addressed for modelling and designing control strategies in manufacturing systems. Among others, the Markov chains (MC) and Petri Nets (PN) can be highlighted given their great application at both process line and plant levels [11]. Despite the great application of both MC and PN in the manufacturing systems, they have been focused on modelling the production states of the machine rather than to model the energy consumption behaviour of such systems.…”

Section: Energy Consumption Modelsmentioning

confidence: 99%

Dual mode control strategy for the energy efficiency of complex and flexible manufacturing systems

Diaz

Ocampo‐Martínez

Olaru

2020

Journal of Manufacturing Systems

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The manufacturing industry is shifting towards smart manufacturing, in which both energy efficiency and flexibility are some of the main objectives of this transformation. In this regard, the control strategies for manufacturing systems should be able to support the requirements of this transformation with a low computational burden towards their implementation in real time. To this end, in this paper, a dual-mode control strategy based on two control approaches is proposed to minimize the energy consumption of manufacturing systems without affecting their productivity, even when scenarios of flexible manufacturing are considered. The first control model is based on Model Predictive Control to determine the optimal and constrained behaviour of the system. Then, the second mode starts from the assumption that the system exhibits a periodic behaviour to switch to an autonomous control mode that not solve an optimisation problem online. The proposed control strategy is tested in a manufacturing process line in which changes in the production programs are considered with the aim to test the performance in flexible manufacturing scenarios. The obtained results show that the computational burden could be significantly reduced while reducing global energy consumption without affecting the system productivity.

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Section: Energy Consumption Modelsmentioning

confidence: 99%

Dual mode control strategy for the energy efficiency of complex and flexible manufacturing systems

Diaz

Ocampo‐Martínez

Olaru

2020

Journal of Manufacturing Systems

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“…In addition to the mentioned simulation approaches, new approaches have been considering for the development of simulations tools, such as Artificial Intelligence (AI) techniques, Petri Nets (PN), and Monte Carlo Simulation (MCS). A detailed explanation of the simulation tools and some applications can be found in [6,94,95,96]. In addition, simulation software such as AnyLogic, Arena, and Flexsim, which are based Table 4: Research topics to improve energy efficiency at the process line level.…”

Section: Strategies and Technologies Of Energy Efficiencymentioning

confidence: 99%

Energy efficiency in discrete-manufacturing systems: Insights, trends, and control strategies

Diaz

Ocampo‐Martínez

2019

Journal of Manufacturing Systems

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Since the depletion of fossil energy sources, rising energy prices, and governmental regulation restrictions, the current manufacturing industry is shifting towards more efficient and sustainable systems. This transformation has promoted the identification of energy saving opportunities and the development of new technologies and strategies oriented to improve the energy efficiency of such systems. This paper outlines and discusses most of the research reported during the last decade regarding energy efficiency in manufacturing systems, the current technologies and strategies to improve that efficiency, identifying and remarking those related to the design of management/control strategies. Based on this fact, this paper aims to provide a review of strategies for reducing energy consumption and optimizing the use of resources within a plant into the context of discrete manufacturing. The review performed concerning the current context of manufacturing systems, control systems implemented, and their transformation towards Industry 4.0 might be useful in both the academic and industrial dimension to identify trends and critical points and suggest further research lines.

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“…Different approaches have been addressed for modeling and designing control strategies in manufacturing systems. Among others, the Markov chains (MC) and Petri Nets (PN) can be highlighted given their great application at both process line and plant levels [20]. The main applications of these approaches have been oriented to model flow lines with a serial movement of jobs among workstations, job shops with more flexibility, assembly lines, among others, which serve as a foundation for design, scheduling, and control.…”

Section: Model Identificationmentioning

confidence: 99%

An optimization-based control strategy for energy efficiency of discrete manufacturing systems

et al. 2019

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In order to reduce the global energy consumption and avoid highest power peaks during operation of manufacturing systems, an optimization-based controller for selective switching on/off of peripheral devices in a test bench that emulates the energy consumption of a periodic system is proposed. First, energy consumption models for the test-bench devices are obtained based on data and subspace identification methods. Next, a control strategy is designed based on both optimization and receding horizon approach, considering the energy consumption models, operating constraints, and the real processes performed by peripheral devices. Thus, a control policy based on dynamical models of peripheral devices is proposed to reduce the energy consumption of the manufacturing systems without sacrificing the productivity. Afterward, the proposed strategy is validated in the test bench and comparing to a typical rule-based control scheme commonly used for these manufacturing systems. Based on the obtained results, reductions near 7% could be achieved allowing improvements in energy efficiency via minimization of the energy costs related to nominal power purchased.

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A classification and review of timed Markov models of manufacturing systems

Cited by 85 publications

References 475 publications

Dual mode control strategy for the energy efficiency of complex and flexible manufacturing systems

Dual mode control strategy for the energy efficiency of complex and flexible manufacturing systems

Energy efficiency in discrete-manufacturing systems: Insights, trends, and control strategies

An optimization-based control strategy for energy efficiency of discrete manufacturing systems

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