A Novel Two‐Stage Flexible Flow Shop Batch Scheduling Model for Grinding Workshops

ABSTRACT The growing need for data storage in data centers has increased the demand for mechanical hard disks due to their low cost and high reliability. Aluminum substrates are the most popular base plates for mechanical hard disks because of their high hardness and low cost. The subtractive grinding process used to produce aluminum substrates consists of two stages: rough grinding and fine grinding. Each stage uses the same number of grinding batch machines, characterized by identical machine capacity and stage‐dependent fixed grinding speeds. The grinding speed during rough grinding is higher than that during fine grinding. The removal thickness for each aluminum substrate falls within a certain interval, and these intervals must overlap when processed in the same batch. The allocation of removal thickness between the two stages determines the batch processing time for each stage, making it a decision variable within a specified interval. Inspired by this process, this paper develops a novel two‐stage flexible flow shop batch scheduling model to improve grinding efficiency and proves it is NP‐hard. Subsequently, we provide two lower bounds. Based on different removal thickness allocation strategies and batch assignment rules, we design five approximation algorithms and analyze their worst‐case performance ratios. Computational experiments demonstrate the varying performance of the proposed algorithms and provide managerial insights for real workshop production.