Energy-efficient scheduling in manufacturing companies: A review and research framework

Gahm, Christian; Denz, Florian; Dirr, Martin; Tuma, Axel

doi:10.1016/j.ejor.2015.07.017

Cited by 359 publications

(138 citation statements)

References 124 publications

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“…Meanwhile, since few years, the research activity has been significantly increasing in the fields of sustainable manufacturing and energy-aware scheduling. As an illustration of this trend, let us mention three recent and complementary surveys (Gahm et al 2015;Giret, Trentesaux, and Prabhu 2015;Schulze et al 2015).…”

Section: Introductionmentioning

confidence: 99%

Energy-aware manufacturing operations

Prabhu

Trentesaux

Taisch

2015

International Journal of Production Research

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This editorial introduces the special issue on energy-aware manufacturing operations in the International Journal of Production Research. The 12 papers in this special issue were selected because of their high quality and also because they deal with topics related to energy-aware manufacturing operations. Three broad challenges are collectively addressed by the papers in this special issue: energy-efficiency vs. manufacturing-system effectiveness in optimisation; the volatility in energy availability, supply and cost; modelling energy consumption in varying scales and across different sub-systems. Previous global discussions about the state of the art in energy-aware manufacturing operations are provided, as well as exploratory guidelines for future research in this area.

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Section: Introductionmentioning

confidence: 99%

Energy-aware manufacturing operations

Prabhu

Trentesaux

Taisch

2015

International Journal of Production Research

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“…While each configuration has accumulated many production scheduling studies, energy efficiency has only been considered in recent years, with the emerging penetration of industrial demand response (Gahm et al, 2016).…”

Section: Literature Reviewmentioning

confidence: 99%

Integrating labor awareness to energy-efficient production scheduling under real-time electricity pricing: An empirical study

Gong

Wee

Pessemier

et al. 2017

Journal of Cleaner Production

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With the penetration of smart grid into factories, energyefficient production scheduling has been emerged. It shifts flexible production loads to lower-priced periods to reduce energy cost for the same production task. However, the existing methods only focus on integrating energy awareness to conventional production scheduling models. They ignore the labor cost which is shift-based and follows an opposite trend of energy cost. For instance, the energy cost is lower during nights while the labor cost is higher. Therefore, this paper proposes a method for energy-efficient and labor-aware production scheduling at the unit process level. This integrated scheduling model is mathematically formulated. Besides the state-based energy model and genetic algorithm-based optimization, a continuous-time shift accumulation heuristic is proposed to synchronize power states and labor shifts. In a case study of a Belgian plastic bottle manufacturer, a set of empirical sensitivity analyses were performed to investigate the impact of energy and labor awareness, as well as the production-related factors that influence the economic performance of a schedule. Furthermore, the demonstration was performed in 9 large-scale test instances, which encompass the cases where energy cost is minor, medium, and major compared to the joint energy and labor cost. The results have proven that the ignorance of labor in existing energy-efficient production scheduling studies increases the joint energy and labor cost, although the energy cost can be minimized. To achieve effective production cost reduction, energy and labor awareness are recommended to be jointly considered in production scheduling. 1Integrating labor awareness to energy-efficient production scheduling under real-time electricity pricing: an empirical study AbstractWith the penetration of smart grid into factories, energy-efficient production scheduling has been emerged. It shifts flexible production loads to lower-priced periods to reduce energy cost for the same production task. However, the existing methods only focus on integrating energy awareness to conventional production scheduling models. They ignore the labor cost which is shift-based and follows an opposite trend of energy cost. For instance, the energy cost is lower during nights while the labor cost is higher. Therefore, this paper proposes a method for energy-efficient and laboraware production scheduling at the unit process level. This integrated scheduling model is mathematically formulated. Besides the state-based energy model and genetic algorithm-based optimization, a continuous-time shift accumulation heuristic is proposed to synchronize power states and labor shifts. In a case study of a Belgian plastic bottle manufacturer, a set of empirical sensitivity analyses were performed to investigate the impact of energy and labor awareness, as well as the production-related factors that influence the economic performance of a schedule. Furthermore, the demonstration was performed in 9 large-scale test instan...

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“…Constraints (6) and (7) restrict the amount of compression and expansion of each job, respectively. Constraints (8) and (9) simultaneously guarantee that only one of compression and expansion for a job is applied to this scheduling problem, which implies that the processing time is either compressed or expanded for each job. Constraint (10) presents non-negativity of variables.…”

Section: Mathematical Modelmentioning

confidence: 99%

“…However, because of increasing costs of energy and environmental pollution, "low-carbon scheduling" as a novel scheduling model has received increasing attention from scholars and engineers [8]. Based on the discussion above, many researchers and manufacturing companies realize the importance of energy efficiency.…”

Section: Introductionmentioning

confidence: 99%

Energy-Efficient Scheduling Problem Using an Effective Hybrid Multi-Objective Evolutionary Algorithm

Yin

et al. 2016

Sustainability

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Nowadays, manufacturing enterprises face the challenge of just-in-time (JIT) production and energy saving. Therefore, study of JIT production and energy consumption is necessary and important in manufacturing sectors. Moreover, energy saving can be attained by the operational method and turn off/on idle machine method, which also increases the complexity of problem solving. Thus, most researchers still focus on small scale problems with one objective: a single machine environment. However, the scheduling problem is a multi-objective optimization problem in real applications. In this paper, a single machine scheduling model with controllable processing and sequence dependence setup times is developed for minimizing the total earliness/tardiness (E/T), cost, and energy consumption simultaneously. An effective multi-objective evolutionary algorithm called local multi-objective evolutionary algorithm (LMOEA) is presented to tackle this multi-objective scheduling problem. To accommodate the characteristic of the problem, a new solution representation is proposed, which can convert discrete combinational problems into continuous problems. Additionally, a multiple local search strategy with self-adaptive mechanism is introduced into the proposed algorithm to enhance the exploitation ability. The performance of the proposed algorithm is evaluated by instances with comparison to other multi-objective meta-heuristics such as Nondominated Sorting Genetic Algorithm II (NSGA-II), Strength Pareto Evolutionary Algorithm 2 (SPEA2), Multiobjective Particle Swarm Optimization (OMOPSO), and Multiobjective Evolutionary Algorithm Based on Decomposition (MOEA/D). Experimental results demonstrate that the proposed LMOEA algorithm outperforms its counterparts for this kind of scheduling problems.

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Energy-efficient scheduling in manufacturing companies: A review and research framework

Cited by 359 publications

References 124 publications

Energy-aware manufacturing operations

Energy-aware manufacturing operations

Integrating labor awareness to energy-efficient production scheduling under real-time electricity pricing: An empirical study

Energy-Efficient Scheduling Problem Using an Effective Hybrid Multi-Objective Evolutionary Algorithm

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