A Job-Shop Scheduling Decision-Making Model for Sustainable Production Planning With Power Constraint
Модель принятия решений для планирования производства в условиях ограничения мощности в системе календарного планирования типа job shop
2021-09-10
SCID: 54.1/bcgyufxw
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job-shop schedulingmakespan minimizationpower-constrained schedulingsustainable production planningvariable machine speed
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Abstract (AI)
Improving environmental sustainability and reducing energy cost are becoming central topics of decision-making in manufacturing. Increasingly manufactures are looking for new solutions that allow them to become more energy efficient and sustainable. Regarding energy cost issue, it is well known that the electricity costs in manufacturing systems strongly depend on the reached peak power. On the other hand, the power required by a manufacturing system affects the adoption of renewable energy sources. The use of renewables, indeed, encompasses fluctuations in energy supply and requires adapting production processes to a power constraint. The article proposes a decision model for the scheduling in a job-shop manufacturing system that simultaneously deals with the power constraint and the variable speed of machine tools. Defining the maximum value of the usable power, decisions can be taken on production scheduling, by adapting the processing speed of several machines that work simultaneously, to the power availability. The model allows decision makers to plan production, taking into account the impossibility of exceeding a certain power and assuming the minimization of the makespan as an objective function. Managers can utilize the scheduling model in all the different contexts, where there is a power limit. The test cases show how the proposed model allows to obtain an efficient scheduling under a constant and variable power constraint. The findings highlight that the model can be employed to reduce the peak power and encourage the use of renewables in manufacturing systems, thus obtaining an efficient scheduling and a more sustainable production.
Key Findings
1
A job-shop scheduling decision model jointly handles power constraints and variable machine-tool speeds during production planning.
2
Production scheduling is optimized by minimizing makespan without exceeding the specified power constraint.
3
Test cases demonstrate efficient schedules under both constant and variable power constraints.
4
The approach can reduce peak power and support renewable-energy adoption, contributing to more sustainable manufacturing.
5
The model adapts the processing speeds of simultaneously operating machines to available power while enforcing a maximum usable-power limit.
Research Object
job-shop manufacturing system with variable-speed machine tools under constant or variable power constraints
Research Subject
sustainable production scheduling that adapts machine processing speeds to power availability while minimizing makespan and reducing peak power
Publication Details
Publication Date
2021-09-10
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