Conference Agenda

In lot streaming, the production lot is divided into smaller batches, each of which can be processed separately through the manufacturing system. Recent studies have shown the practical relevance of lot streaming by providing greater flexibility in scheduling and allowing for more efficient use of available resources. This research addresses the potential of lot streaming within the hybrid flow shop scheduling problem by integrating setup times, with a focus on minimizing the makespan. The study proposes a mixed integer linear programming formulation to capture the complexity of the problem and employs a metaheuristic iterated greedy algorithm to efficiently find near-optimal solutions. A key aspect of this investigation is the consideration of (non-anticipatory) setup times, which occur between every changeover of sublots and add a layer of realism to the problem. The effectiveness of the proposed approach is evaluated through computational experiments comparing different local reinforcement strategies and sublot assignment methods. The results allow quantification of the potential of lot streaming within hybrid flow shops. Insights from the experiments highlight the impact of factors such as the size and number of sublots on the quality of the solution, suggesting potential avenues for practical implementation in multi-stage manufacturing systems.

The trend to distribute production facilities across several countries, due to globalization and increasing customer demands, increases the complexity of operational processes and presents companies with the challenge of effectively managing these production networks. Due to the complexity of the scheduling problems, there has been a growing research interest in investigating centralized solution approaches for production networks. This paper extends the fundamental problems by integrating factory eligibility constraints as well as options to qualify factories by relocating tools or personnel for a distributed permutation flow shop problem. A bi-criteria optimization problem is analyzed to minimize weighted total tardiness and total cost. Another unique feature is the integration of pricing of carbon emissions due to production, tool transfer and transport to the customer.

Factory-dependent due dates, limited transport capacity for tool transfer, and transport time windows strengthen the practical relevance. A computational study is used to analyze the impact and dependencies of critical influencing variables such as customer location, tool and product weight and production process intensity. In addition, the effect of restricting the tool transfer options on the Pareto front is analyzed. A key implication is the dependence of scheduling decisions on critical contextual factors such as customer location, degree of factory eligibility, and tool and product weight, highlighting the need to consider transportation as a decisive factor in distributed scheduling problems. Consequently, a promising area for further research is the potential to investigate the integration of information on critical instance parameters to guide the search in approximation-based solution methods.

The design of flow lines is an extensive area of research whereby most publications focus on buffer allocation to cope with random influences like breakdowns or random differences in processing times. In addition, spare parts can directly increase the machines' availability. However, only a few papers consider the simultaneous optimization of buffer space and the possible number of spare parts in stock. The literature hardly even considers the evaluation of such systems. We are the first to introduce the joint optimization of buffer space and spare parts for flow lines of arbitrary length. First, we aim to allocate buffer capacities and spare parts efficiently. Since the buffer allocation problem is NP-hard, we can expect only to find near-optimal solutions. Second, we demonstrate the algorithmic behavior of different greedy and metaheuristics on this design problem. We illustrate how to exploit the problem structure to solve it almost optimally. Third, we generate managerial insights into allocating spare parts in manufacturing systems with buffers. We show that spare parts tend to be more effective when arranged at or near the center of a flow line, as it is already known for buffers. Moreover, we provide details on the combined buffer and spare part allocations.