Layout design for flexible manufacturing systems considering single-loop directional flow patterns

Facility layout design problems in flexible manufacturing systems (FMS) differ from traditional facility design problems and are more difficult to solve because there are more constraints that must be considered (i.e., cell shape, cell orientation, pick-up and drop-off point positions). The focus of this paper is on the closed loop type layout, which is based on a predetermined layout pattern. This layout pattern is commonly found in manufacturing settings since it requires a simplified material handling system configuration and since it facilitates a modular and expandable layout structure. The open-field type layout problem, where there is no predetermined layout pattern, may potentially have a more efficient configuration, since there are fewer restrictions. However, this problem is more difficult to solve and may result in configurations that are not desirable due to the lack of structure or modularity. The procedure developed in this paper improves the efficiency of the closed loop configuration by changing the rectangular shape of the loop to different sizes. In many cases, the resulting closed loop layout proves to be as efficient as the open field layout. A simulated annealing procedure (SA-CL) is used to search for the configuration that minimizes the total material handling costs. A comparison of the results with existing methods indicates that, based on solution quality and computational time, the SA-CL offers a favourable alternative for efficient layout design.

This paper describes the ways of using program tools for design and simulation of flexible manufacturing systems (FMS) for the purpose of teaching the undergraduate course Flexible Manufacturing Systems. The concept of the course is based on the synergism of theoretical knowledge and practical hands-on experience gained by studying numerous problem cases, using common tools for description of FMS (Petri nets, max-plus algebra and matrix modeling) and by working with more specialized program tools for FMS design and simulation. An emphasis is given to the description o the program tool FlexMan that enables elegant setting of an FMS configuration, supports automatic generation of a matrix-based FMS description and consequently, enables effective off-site design and simulation of the FMS by using virtual reality models and Internet-related technologies.

Although a significant amount of simulation research has been carried out for design and analysis of flexible manufacturing systems (FMS), it does not provide optimal solutions. In this research, we employ two optimum-seeking methods to design and optimize a manufacturing system. The first method is a Taguchi approach, which uses robust design concept to reduce the output variation. The second method is the response surface methodology (RSM), which combines mathematical and statistical techniques to study the geography of the response surface. The results show that throughput of a selected FMS system can be maximized when both methods are employed.

With the advance of research, design and operation of flexible manufacturing systems (FMS) which are designed to produce a variety of different part types with high machine utilization, short lead times and little work-in-progress inventory, new requirements like high modeling efficiency, high model validity and credibility and effectiveness and correct analysis of results are defined. Simulation is an efficient tool to verify design concepts, to select machinery, to evaluate alternative configurations and to test system control strategies of an FMS, etc. This paper presents a useful tool for simulating the behavior of random FMSs. This simulator is used for real time alternative routing selection based on a group of metaheuristics principles which include in particular simulated annealing (SA), genetic algorithm (GA), taboo search (TS), ant colony algorithms (ACO), particle swarm optimization (PSO) and electromagnetism like method (EM). This software is also can used for performance and sensitivity analysis of theses techniques jugged by the production rate, machines and material handling utilization rate, the cycle time and the work in process.

Flexible manufacturing system (FMS) was defined as highly automated group technology machine cell, consisting of a group of processing stations interconnected by an automated material handling and storage system, and controlled by an integrated computer system. FMS can produce parts or products are in the mid-volume, mid-variety production range. The layout system in FMS is an important criterion to design the FMS system to produce a part or product. This facility layout of an FMS involves the positioning of cells within given boundaries, so as to minimize the total projected travel time between cells. Defining the layout includes specifying the spatial coordinates of each cell, its orientation in either a horizontal or vertical position, and the location of its load or unloads point. There are many types of FMS layout such as In-line, loop ladder and robot centered cell layout. The research is concentrating on the design and optimization FMS layout. The final conclusion can be summarized that the objective to design and optimisation of FMS layout for this study is successful because the FMS In-line layout is the best layout based on effective time and cost using ARENA simulation software.

A new FMS simulator with object-oriented-programming techniques

A well-planned arrangement of manufacturing departments on a two-dimensional planar region considerably increases the efficiency of its production systems, which is termed facility layout problem (FLP). Conventional layout design approach often designs intercell layout (determining exact location of each department on shop floor area) and flow path layout design of material handling system (MHS) step by step in a sequential manner. This results in suboptimal solutions for FLP. In this paper, an integrated approach is adopted to design the intercell layout and the flow path layout of MHS simultaneously. The quality of the final layout is evaluated by minimizing total material handling cost. Sequence pair (SP) representation is used for layout encoding. The translation from SP to layout is efficiently made by longest common subsequence (LCS) methodology. An elitist strategy genetic algorithm using simulated annealing (E-GASAA) as a local search mechanism is developed and tested with four test problem instances available in the literature. Elitist strategy is incorporated to enhance convergence characteristic of the proposed algorithm. It is found that the proposed E-GASAA is able to produce best solutions consistently for the test problem instance of different sizes within acceptable computational effort. In addition to that, we tried to reduce the computational load with the help of adopted LCS computation methodology and achieved a good improvement.

Solving a group layout design model of a dynamic cellular manufacturing system with alternative process routings, lot splitting and flexible reconfiguration by simulated annealing

SUMMARY The material handling system of a flexible manufacturing system (FMS)consists of load and unload mechanisms, transfer mechanisms, and internal storage facilities, each of which may be configured in many different ways. In addition, many options are available for dispatching work-parts between work-stations. The inherent flexibility of an FMS affords the opportunity for enhanced system efficiency, yet it also makes the analysis and design of the system extraordinarily complex and difficult. This paper develops a combined process interaction-discrete event simulation model to analyse the material handling and dispatching system of an FMS. The model is implemented in SLAM (Simulation Language for Alternative Modeling)The SLAM model is applied to an example FMS and is shown to be an effective tool for designing the material handling system and for selecting the appropriate work-part dispatching option. It provides greater flexibility in both modelling and output analysis than conventional process inte...

One of the basic components of Industry 4.0 is the design of a flexible manufacturing system (FMS), which involves the choice of parameters to optimize its performance. Discrete event simulation (DES) models allow the user to understand the operation of dynamic and stochastic system performance and to support FMS diagnostics and design. In combination with DES models, optimization methods are often used to search for the optimal designs, which, above all, involve more than one objective function to be optimized simultaneously. These methods are called the multi-objective simulation–optimization (MOSO) method. Numerous MOSO methods have been developed in the literature, which spawned many proposed MOSO methods classifications. However, the performance of these methods is not guaranteed because there is an absence of comparative studies. Moreover, previous classifications have been focused on general MOSO methods and rarely related to the specific area of manufacturing design. For this reason, a new conceptual classification of MOSO used in FMS design is proposed. After that, four MOSO methods are selected, according to this classification, and compared through a detailed case study related to the FMS design problem. All of these methods studied are based on Design of Experiments (DoE). Two of them are metamodel-based approaches that integrate Goal Programming (GP) and Desirability Function (DF), respectively. The other two methods are not metamodel-based approaches, which integrate Gray Relational Analysis (GRA) and the VIKOR method, respectively. The comparative results show that the GP and VIKOR methods can result in better optimization than DF and GRA methods. Thus, the use of the simulation metamodel cannot prove its superiority in all situations.

The objective of this research is to design and implement real-time scheduling algorithms for flexible manufacturing systems. Four CNC machines with a load/unload station and a conveyor belt are combined as a flexible manufacturing system. Three fuzzy-based scheduling algorithms have been developed for operation sequencing, task sequencing and routing. LabVIEW environment has been used for the system modelling and testing. Several case studies have been carried out to test and verify the flexibility of the system and the effectiveness of the proposed schedulers. The obtained results indicate that the proposed scheduling algorithms for sequencing and routing are promising for such FMS. The performances of the proposed fuzzy scheduling algorithms are compared with those obtained from published literature.

We describe here a systematic method for the design and modeling of flexible manufacturing systems, using object-oriented concepts and Petri nets. We first define the system components in terms of an object model consisting of hierarchical sets of classes and associations. Then, we model the dynamic aspects of the system using statecharts, including exceptions and abnormal behavior. As a third step, we derive Petri nets from those statecharts to realize the concurrency present in the system. Finally we develop a hierarchy of controllers, corresponding to the layers of the object model, for the independent components of the system based on the Petri nets obtained in the previous step. The approach is systematic and relatively easy to apply. It is illustrated through a realistic example. >

The formation of machine–part families is an important task in the design of cellular and flexible manufacturing systems. The formation results in the creation of many benefits for manufacturing systems. Among the many methods utilised in machine–cells formation, the similarity coefficient method (SCM) is most widely used. When SCM is used, the rearrangement of machine and part components is required to form machine–part families. This process of rearrangement has been considered as being subjective and difficult, may result in improper assignments to parts families, resulting in a negation of benefits promised. This paper presents an effective algorithm to identify part–families and bottleneck parts, given machine groupings, rather than addressing the machine grouping problem in general.

Flexible manufacturing systems (FMS) consists of a set of numerically controlled machines, material handling systems (MHS), information system and service centres all working towards a common production schedule goal being the achievement of economic product manufacture in short period of time[1]. An FMS is highly versatile production system capable of performing many different operations given the proper tooling, fixtures and materials. Another feature of this system is the short switching time between different operations assigned to its individual workstations. An FMS to function effectively must have an on-line control system capable of reacting quickly to any problem occurring in the system by providing decisions to deal with the problem in a short period of time. The FMS control system thus needs to receive accurate and reliable information from the shop floor. The operational control of an FMS in general involves accessing a large set of static and dynamic data, and requires complex control algorithms. This paper presents a control system developed for real-time operational control of an FMS. The system is organised hierarchically, each level responsible for making decisions according to the operational needs and the time criticality of the particular level. The overall aim of the control system is to optimise FMS performance while meeting the production requirements.

The design and operation of flexible manufacturing systems (FMS): Paul Ránky