Intelligent systems in manufacturing: current developments and future prospects

Global competition and rapidly changing customer requirements are demanding increasing changes in manufacturing environments. Enterprises are required to constantly redesign their products and continuously reconfigure their manufacturing systems. Traditional approaches to manufacturing systems do not fully satisfy this new situation. Many authors have proposed that artificial intelligence will bring the flexibility and efficiency needed by manufacturing systems. This paper is a review of artificial intelligence techniques used in manufacturing systems. The paper first defines the components of a simplified intelligent manufacturing systems (IMS), the different Artificial Intelligence (AI) techniques to be considered and then shows how these AI techniques are used for the components of IMS

Determination of Routing and Sequencing in a Flexible Manufacturing System Based on Fuzzy Logic

AbstractThis paper is concerned with scheduling in Flexible Manufacturing Systems (FMS) using a Fuzzy Logic (FL) approach. Four fuzzy input variables; machine allocated processing time, machine priority, machine available time and transportationpriority are defined. The job priority is the fuzzy output variable, showing the priority status of a job to be selected for next operation on a machine. The model will first assign operation of parts to machines under the given production plan and then determine the input sequence of the assigned operations for each machine based on a multi-criteria scheduling scheme. A complete fuzzy scheduling algorithm is developed to solve the operation allocation and operation scheduling problems in FMS environments aiming to approach the objectives of minimizing mean flowtime, maximizing machine utilization and balancing machine usage. The test results demonstrate the superiority of the fuzzy logic approach in most performance measures.

Scheduling and discrete event control of flexible manufacturing systems based on Petri nets

A flexible manufacturing system (FMS) is a computerized production system that can simultaneously manufacture multiple types of products using various resources such as robots and multi-purpose machines. The central problems associated with design of flexible manufacturing systems are related to process planning, scheduling, coordination control, and monitoring. Many methods exist for scheduling and control of flexible manufacturing systems, although very few methods have addressed the complexity of whole FMS operations. This thesis presents a Petri net based method for deadlock-free scheduling and discrete event control of flexible manufacturing systems. A significant advantage of Petri net based methods is their powerful modeling capability. Petri nets can explicitly and concisely model the concurrent and asynchronous activities, multi-layer resource sharing, routing flexibility, limited buffers and precedence constraints in FMSs. Petri nets can also provide an explicit way for considering deadlock situations in FMSs, and thus facilitate significantly the design of a deadlock-free scheduling and control system. The contributions of this work are multifold. First, it develops a methodology for discrete event controller synthesis for flexible manufacturing systems in a timed Petri net framework. The resulting Petri nets have the desired qualitative properties of liveness, boundedness (safeness), and reversibility, which imply freedom from deadlock, no capacity overflow, and cyclic behavior, respectively. This precludes the costly mathematical analysis for these properties and reduces on-line computation overhead to avoid deadlocks. The performance and sensitivity of resulting Petri nets, thus corresponding control systems, are evaluated. Second, it introduces a hybrid heuristic search algorithm based on Petri nets for deadlock-free scheduling of flexible manufacturing systems. The issues such as deadlock, routing flexibility, multiple lot size, limited buffer size and material handling (loading/unloading) are explored. Third, it proposes a way to employ fuzzy dispatching rules in a Petri net framework for multi-criterion scheduling. Finally, it shows the effectiveness of the developed methods through several manufacturing system examples compared with benchmark dispatching rules, integer programming and Lagrangian relaxation approaches

A hybrid CFGTSA based approach for scheduling problem: a case study of an automobile industry

In the global competitive world swift, reliable and cost effective production subject to uncertain situations, through an appropriate management of the available resources, has turned out to be the necessity for surviving in the market. This inspired the development of the more efficient and robust methods to counteract the existing complexities prevailing in the market. The present paper proposes a hybrid CFGTSA algorithm inheriting the salient features of GA, TS, SA, and chaotic theory to solve the complex scheduling problems commonly faced by most of the manufacturing industries. The proposed CFGTSA algorithm has been tested on a scheduling problem of an automobile industry, and its efficacy has been shown by comparing the results with GA, SA, TS, GTS, and hybrid TSA algorithms

Performance Analysis of An Experimental Micro Flexible Manufacturing System (FMS)

Due to advanced technology, it is very important the performance of FMS for sensivity, production quality, repeatability and energy consumptions. Flexible manufacturing systems (FMSs) are the most automated and technologically sophisticated of the machine cell types used to implement cellular manufacturing. An FMS usually has multiple automated stations and is capable of variable routings among stations, while its flexibility allows it to operate as a mixed model system. The FMS concept integrates many of the advanced technologies that we met in previous units, including flexible automation, CNC machines, distributed computer control, and automated material handling and storage. In this experimental investigation, vibration and accelerations analysis of an experimental FMS with 5 degrees of freedom robot manipulator are presented. Firstly, experimental measurement of accelerations and vibrations are trained with a vibration measurement system and sensors. However, the process of production of part is a cycle of exact production time

A study of the robustness of the group scheduling method using an emulation of a complex FMS

International audienceIn the field of predictive-reactive scheduling methods, group sequencing is reputed to be robust (in terms of uncertainties absorption) due to the flexibility it adds with regard to the sequence of operations. However, this assumption has been established on experiments made on simple theoretical examples. The aim of this paper is to carry out experimentation on a complex flexible manufacturing system in order to determine whether or not the flexibility of the group scheduling method can in fact absorb uncertainties. In the study, transportation times of parts between machines are considered as uncertain. Simulation studies have been designed in order to evaluate the relationship between flexibility and the ability to absorb uncertainties. Comparisons are made between schedules generated using the group sequencing method with different flexibility levels and a schedule with no flexibility. A last schedule takes into account uncertainties whereas schedules generated using the group sequencing method do not. As it is the best possible schedule, it provides a lower bound and enables to calculate the degradation of performance of calculated schedules. The results show that group sequencing perform very well, enabling the quality of the schedule to be improved, especially when the level of uncertainty of the problem increases. The results also show that flexibility is the key factor for robustness. The rise in the level of flexibility increases the robustness of the schedule towards the uncertainties

The investigation of the effect of scheduling rules on FMS performance

The application of Flexible Manufacturing Systems (FMSs) has an effect in competitiveness, not only of individual companies but of those countries whose manufactured exports play a significant part in their economy (Hartley, 1984). However, the increasing use of FM Ss to effectively provide customers with diversified products has created a significant set of operational challenges for managers (Mahmoodi et al., 1999). In more recent years therefore, there has been a concentration of effort on FMS scheduling without which the benefits of an FMS cannot be realized. The objective of the reported research is to investigate and extend the contribution which can be made to the FMS scheduling problem through the implementation of computer-based experiments that consider real-time situations. [Continues.

Dynamic Scheduling of Flexible Manufacturing Systems

To date, group scheduling research has primarily focused on examining the performance of different group heuristics under various experimental conditions. However, the dynamic selection of group heuristics has not received sufficient attention from researchers. The objective of this paper is to demonstrate a mechanism for the dynamic selection of group heuristics from several candidate alternatives by exploiting real time information from the Flexible Manufacturing System (FMS). In this regard, two tools, viz., Analytic Hierarchy Process (AHP) and Simple Multi-Attribute Rating Technique Exploiting Ranks (SMARTER), are used to develop models for part type and family selection. The experimental results indicate that the performance of the proposed models are better than the common group scheduling heuristics under varied experimental conditions.Singapore-MIT Alliance (SMA

An Integrated Approach for the Analysis of Manufacturing System States

With advancement in the manufacturing technology and rise in the purchasing ability, demand for newer products is increasing continuously. This is forcing manufacturing companies to persistently look for new techniques to improve the productivity of a manufacturing system and ensure optimum utilization of all the elements of a manufacturing system, including facility layout. Traditional research had viewed facility layout, material handling and productivity improvement as separate activities.  Researchers depending on their area of specialization focused on either the production aspects of a company, the material handling aspects or facility layout. However, to ensure productivity, this study proposes a new theory to analyze the current state of the system with an integrated approach of production system and material handling system. In this study, the current state of the system is classified into three different states and a methodology is proposed to identify the current state of the system. This new theory can be used by manufacturers to identify appropriate strategies for improving productivity.  The identification of the state of the system is necessary for effective improvement of the system