Scheduling an automatic IoT manufacturing system with multiple servers

Fully automatic manufacturing systems have received wide attention and are being adopted rapidly in manufacturing industry with the application of Internet of Things. How to coordinate correlated operations efficiently has become a prominent challenge for many practitioners. In this regard, this paper considers an optimal control issue arising in a fully automatic manufacturing system based on Internet of Things and formulates it as a novel parallel machine scheduling problem with multiple servers. The setup stage and the removal stage of a job must be performed by one of the servers on one of the machines while the processing stage of the job can be performed automatically by the machine. The problem takes maximum slack times, machine availability, server availability, machine eligibility, and server eligibility into consideration simultaneously and its objective is to minimize makespan. The problem generalizes a number of problems in the topic of server scheduling. To obtain optimal solutions, a mixed integer programming model is provided. To facilitate the development of heuristic algorithms, the classical list-and-assign technique in this new problem setting is deeply analyzed. Six heuristic algorithms are proposed based on the technique. Numerical experiment shows that it is advantageous to list the jobs according to non-increasing order of setup time or according to non-increasing order of the sum of setup time and removal time.