Determining the Minimum Waiting Times in a Hybrid Flow Shop Using Simulation-Optimization Approach

Planning the order and size of batches is an extremely complex task especially if these tasks are related to production companies in a real environment. This research deals with the problem of determining the entry order and size of product batches in order to optimize inter-operational waits, in the form of waiting in queues for processing and waiting due to the setting-up of the workplace. In real environment, these waits represent a large share of the time spent in the production of a unit of product in a hybrid flow shop. This problem is almost impossible to be solved with analytical models because they may require many simplifying assumptions. Therefore, a simulation-optimization approach is used to solve this problem. Discrete event simulation allows greater flexibility in the representation of the real production system, while the integrated optimization tool, a genetic algorithm, serves to find the optimal solution relatively quickly. To ensure simpler production management, batch size is defined as a fixed value with the exception of a different first or last batch which represents the difference to the required production volume. Therefore, two optimization cases are presented in the paper. Although both cases show improvements, the case when a different batch is the first batch shows better results. In that case, the share of setup time in the total production time of the product unit was reduced from 4% to 3%, and the share of waiting time in the queue for processing was reduced from 76% to 32%

Facilitated post-model coding in discrete event simulation (DES): a case study in healthcare

Research on facilitated discrete event simulation (DES) is gathering pace but there is still a need to put forward real examples to explain the process to newcomers. This paper is part of a line of research on the methodology of facilitated DES. In this paper we explain in more detail the facilitation process and the tools used to support the experimentation and implementation stages in a DES study involving workshops with a group of stakeholders, after an initial simulation model has been coded on the computer. A real case study is used to describe the process followed and the interactions at the workshops. Extracts from the transcripts are also included, with the view to providing evidence of the stakeholders’ involvement and their mood during the workshops. We conclude with a discussion on the process and tools used to support the facilitation process. Future research directions are also put forward

RFID for returnable container management in the automotive industry: A Discrete-Event Simulation approach

Returnable containers are a critical factor to ensure quality of manufacturing operations in the automotive industry. However, containers management is still affected by chronic issues, such as containers shortage, losses or inefficient handling. Research and industry experts agree the “Achilles’s heel” of current practice is the lack of accurate and timely data about containers flow throughout the complex automotive supply chain. Moreover, containers handling operations still rely on manual operations. Radio Frequency Identification (RFID) is a technology that allows for automatic extraction of items flow data at key points along the supply chain, without the need of manual operations, and represents a very interesting solution for returnable containers management. RFID has already been employed in many different sectors, since giants as Wal-Mart or the United States (U.S.) Department of Defense adopted it for their supply-chain. Several approaches have been adopted in literature to explore potential applications of this technology, but few studies focus on automotive returnable containers management. In this work, a Discrete-Event Simulation (DES) approach is proposed to evaluate the impact of RFID on automotive returnable containers supply chain. The model has been developed in collaboration with Fiat Chrysler Automobiles (FCA). Applying factorial design and ANOVA relevant benefits of using RFID have been identified. The same model has been used to define main influencing factors in containers supply chain performance