Selection of cutting conditions for power constrained parallel machine scheduling. (February 2017)

• Record Type: Journal Article
• Authors: Wang, Yi-Chi; Wang, Ming-Jun; Lin, Sung-Chi
• Is Part Of: Robotics and computer-integrated manufacturing. Volume 43(2017)
• Page Start: 105
• Page End: 110
• Publication Date: 2017-02
• Subjects: Cutting conditions -- Parallel machine scheduling -- Power demand -- Genetic algorithm; Robots, Industrial -- Periodicals; Computer integrated manufacturing systems -- Periodicals; Robotics -- Periodicals; Robots industriels -- Périodiques; Productique -- Périodiques; Robotique -- Périodiques; 670.285
• DOI: 10.1016/j.rcim.2015.10.010
• Languages: English
• ISSNs: 0736-5845

Abstract

Abstract: Most previous studies on machining optimization focused on aspects related to machining efficiency and economics, without accounting for environmental considerations. Higher cutting speed is usually desirable to maximize machining productivity, but this requires a high power load peak. In Taiwan, electricity prices rise sharply if instantaneous power demand exceeds contract capacity. Many studies over the previous decades have examined production scheduling problems. However, most such studies focused on well-defined jobs with known processing times. In addition, traditional sequencing and scheduling models focus primarily on economic objectives and largely disregard environmental issues raised by production scheduling problems. This study investigates a parallel machine scheduling problem for a manufacturing system with a bounded power demand peak. The challenge is to simultaneously determine proper cutting conditions for various jobs and assign them to machines for processing under the condition that power consumption never exceed the electricity load limit. A two-stage heuristic approach is proposed to solve the parallel machine scheduling problem with the goal of minimizing makespan. The heuristic performance is tested by distributing 20 jobs over 3 machines with four possible cutting parameter settings. Highlights: This study investigates a parallel machine scheduling problem for a manufacturing system with a bounded power demand peak. The problem is to simultaneously determine proper cutting conditions for various jobs and assign them to machines for processing under the condition that power consumption never exceed the electricity load limit. A two-stage heuristic approach is proposed to solve the production scheduling problem with the goal of minimizing makespan. With the proposed approach for production scheduling, the power demand is balanced perfectly without exceeding the given upper bound.