The mobile phone is a typical 3C electronic product characterized by frequent replacement, multiple product specifications, high flexibility, high-frequency production line switching, and urgent delivery time during production. Therefore, the optimized design of the mobile phone production workshop is crucial. This paper takes the assembly process of a specific type of mobile phone assembly as the research object and adopts the heuristic balance method to combine the production procedures. Moreover, it considers the automation degree of the process and the demand for production line rhythm to carry out station division and working hours design for the assembly process. The advantages and disadvantages of the plug-and-play production line and unit production line architecture are integrated, aiming at the production line’s construction cost and unit area capacity. A hybrid workshop with a mixed combination of two types of production lines is designed and an optimization model of hybrid workshop design is established. The semi-physical simulation technology of digital twins is utilized to verify the proposed design scheme to achieve the balance optimization of the production line, improve production efficiency, and reduce production costs. This work provides a technical scheme for designing and optimizing large-scale mobile phone assembly workshops with multi-batch and high-frequency production changes.

Simultaneous optimisation of machines and buffers in a large series-parallel production line is an NP-hard problem. The formulated optimisation model in this study is used to minimise the total investment cost subject to the desired throughput rate and cycle time by optimising the machine types, number of parallel machines, and buffer capacities. To solve this kind of design problem, a decomposition-coordination method is proposed to efficiently and accurately generate allocation solutions for large production lines. The proposed method includes two iterative processes: the decomposition process decouples the original line into several small lines and optimises them separately, while the coordination process ensures that the optimisation problems of the decomposed lines are similar to the corresponding part of the original. The performance of this approach is demonstrated through numerical experiments by comparisons with the simulated annealing algorithm and non-dominated sorting genetic algorithm-II. Finally, the sets of numerical results and a multi-factorial experimental analysis illustrate the influences of target system parameters on the resource configurations.