یک مدل غیر متمرکز برای تولید جریان فروشگاه با سیستم حمل و نقل قابل انعطاف

The recent advances in technology sectors often clash with traditional organizational paradigms which can limit or make difficult an efficient implementation in the real world. In this paper we show how it is possible to exploit the advantages of innovative technologies in manufacturing when these are supported by new and efficient methods for production management. More in details, we face a flow shop scheduling problem in a shoe manufacturing system in which overtaking of jobs is allowed thanks to an innovative transportation system. Overtaking means that a job can be put in waiting state and another job can surpass it, allowing the change of the scheduling sequence. Preemption is not allowed. The objective function of the problem is the minimization of the maximum lateness. We propose a decentralized model, based on multi-agent system theory, to represent the production cells of the plant and to include the potentiality offered by overtaking of jobs at decisional level. The adoption of a decentralized approach increases the system flexibility since each machine is able to solve its local scheduling problem. Adding or removing machines to the plant will not imply a change in the scheduling algorithms. The outcomes of this work are reached firstly through a formulation of the problem with three flow shop scheduling models, secondly through a comparison of the models with respect to different performance indicators. The results highlight as the decentralized approach is able to reach comparable performances with the centralized one for a relevant number of instances. Moreover sensitivity analysis shows as in the decentralized model the computational time required to solve bigger instances increases less quickly than in the case of centralized ones. Finally, simulations of the decentralized approach clarify as the correlation of the local solution procedure is effected by the number of machines of the flow shop and the coordination mechanism is effected by the number of the jobs to be scheduled.

The concept of flexible manufacturing system (FMS) was introduced in response to the need for greater responsiveness to changes in products, production technologies and markets, and has been deeply discussed in the literature [1], [2], [3] and [4]. FMSs have a high degree of complexity and they are often underused mostly due to lack in software systems and communication technologies able to effectively manage the complexity. For this reason it is common to analyze the FMS along two different dimensions: the flexibility and the complexity. The former dimension can be analyzed as internal flexibility (i.e., the ability to manage in efficient way the plant) and external flexibility (i.e., the ability to quickly respond to the market requests). The latter dimension, i.e., the complexity, is instead measured in terms of (i) plant complexity and, (ii) information domain complexity. The plant complexity is an indicator of the number of machines, products, and product models [5]. The information domain complexity is a function of total quantity of information, information diversity, and information content, corresponding to the effort to capture and to transfer in useful format the information [6].

This work presented three models able to solve the flow shop scheduling problem. Three mathematical models have been formulated and solved with the aim to compare them in terms of ability to exploit the opportunities offered by an innovative transportation line in a shoe manufacturing plant. In particular two model settings, i.e., centralized and decentralized, have been compared. The permutation (FS) and general flow shop (GFS) scheduling problem formulations have been derived from Manne's research works. The “cascade” model (CFS) is proposed by the authors of this paper. As reported in Section 6, it is possible to reach the following findings.