Manufacturing-oriented silicon steel coil lengthwise cutting stock problem with useable leftover. Issue 2 (24th August 2021)

• Record Type: Journal Article
• Authors: Li, Fengjie; Chen, Yan; Hu, Xiaochun
• Is Part Of: Engineering computations. Volume 39:Issue 2(2022)
• Page Start: 477
• Page End: 492
• Publication Date: 2021-08-24
• Subjects: Industrial manufacturing -- Cutting stock problem -- Silicon steel coil -- Lengthwise cutting -- Leftovers utilization correction; Computer-aided engineering -- Periodicals; Computer graphics -- Periodicals; 620.00285
• DOI: 10.1108/EC-11-2020-0660
• Languages: English
• ISSNs: 0264-4401

Abstract

Abstract : Purpose: This paper propose an algorithm for the multiple silicon steel coils multiperiod two-dimensional lengthwise cutting stock problem (m2DLCSP), so as to minimize the total cost of materials and production. Design/methodology/approach: The authors propose a sequential leftovers utilization correction (SLUC) algorithm for the m2DLCSP. The algorithm primarily considers three optimization strategies. First, it considers usable leftovers to simplify the cutting process and improve material utilization. The total quantity and types of leftovers should be limited in order to avoid leftover overstock. Second, it uses a splice method of items to improve the generated cutting plan. Third, it takes into account operational restrictions in the cutting operations. Operational restrictions include imposing maximum and minimum lengths on the cutting patterns, and the limitation of cutting knives at the slitting machines. Findings: Several sets of benchmark with real-world and randomly generated instances are provided to evaluate the algorithm. Compared with literature algorithm and current procedure applied in enterprises, the computational results indicate that proposed algorithm can effectively reduce the total cost, and the computation time is reasonable for practical use. Social implications: This algorithm can effectively reduce the total cost. Originality/value: The proposed method can effectively applied to solve the m2DLCSP and improve the economic efficiency of enterprises.