Job shop scheduling using fuzzy logic

Abstract

In a flexible manufacturing system (FMS) scheduling problems become extremely complex, even for simple breakdowns, when dynamic uncertainties such as machine breakdowns and the uncertain arrival of jobs are taken into consideration. In the first stage of this study, a fuzzy logic-based algorithm for assigning priorities to part types that are to be machined is proposed. In the second stage, an operation-machine allocation and scheduling algorithm is presented. A criteria contribution equalizer is used in decision-making. The proposed algorithm can re-generate the schedule in case of a machine breakdown, and therefore can be used as an on-line controller. The system architecture and linguistic variables are presented and results showed that the proposed algorithm improves the system efficiency.

Fuzzy logic in production sequencing: the case of a cosmetics manufacturer in Brazil

“…Nowadays, fuzzy systems are used in a wide variety of situations and technologies, such as in the design and operation of consumer products (e.g., washing machines and cameras), in industrial controls (e.g., elevators), in large public systems (e.g., the subway) and in medical devices (e.g., cardiac pacemakers) (McNeill and Thro, 1994). Despite the numerous fields of application, one of the most significant and successful filed where fuzzy logic is used is control problems (Bilkay et al, 2004;Ross, 2004). One recent example is Rodger et al (2014) who provides an interesting example of the use of fuzzy-logic in inventory control to reduce back orders of spare parts.…”

“…Such complexity makes the use of conventional mathematical methods more problematic (Bilkay et al, 2004;Ross, 2004) or insufficient. The use of fuzzy logic to model production control systems is also justified by the ability of fuzzy logic to capture and apply the experience/knowledge of the human experts (e.g., the production system managers) (Verbruggen and Bruijn, 1997).…”

“…Summarising, the complexity and uncertainty of a production environment make fuzzy logic an interesting heuristic technique to circumvent the difficulties and computational costs related to the optimisation of sequencing by traditional stochastic techniques (Dobois et al, 2003;Bilkay et al, 2004).…”

“…The author developed a production control system based on fuzzy logic principles. Despite the numerous fields of application of fuzzy logic, possibly the most significant and successful ones focused on control problems (Bilkay et al, 2004;Ross, 2004).…”

“…A production control system based on fuzzy logic also has the ability to overcome computational difficulties and costs related to the optimisation of stochastic techniques-based sequencing (Dubois et al, 2003;Bilkay et al, 2004). In addition to being able to capture (at least part of) the complexity of a production system, a control tool based on fuzzy logic has also the potential to allow for greater dynamism in decision making (for e.g., with easier and faster re-sequencing in response to environmental changes whenever needed).…”