Vehicle positioning in cell manufacturing systems via robust optimization

Numerous manufacturing companies are taking advantage of material handling systems due to their flexibility, reliability, safety and contribution to the increase of productivity. However, several uncertain parameters such as types of cost, availability of vehicle etc., influence the performance of the material handling system greatly. In recent years, robust optimization has proven to be an effective methodology permitting overcoming uncertainty in optimization models. Robust optimization models work well even when probabilistic knowledge of the phenomenon is incomplete. This paper thus proposes two new zero-one programming (ZOP) models for vehicle positioning in multi-cell automated manufacturing system. Uncertain parameters in these models include cost parameters, travel time between each pair of centers of cells and location of machines, average time required for performing all transports from location of machines and availability of the vehicle. Then, the robust counterpart of the proposed ZOP models is presented by using the recent extensions in robust optimization theory. Eventually, to verify the robustness of the solutions obtained by the novel robust optimization model, they are compared to those generated by the deterministic ZOP model for different test problems.     

Perturbation analysis for production control and optimization of manufacturing systems

We use stochastic fluid models (SFM) to capture the operation of threshold-based production control policies in manufacturing systems without resorting to detailed discrete event models. By applying infinitesimal perturbation analysis (IPA) to a SFM of a workcenter, we derive gradient estimators of throughput and buffer overflow metrics with respect to production control parameters. It is shown that these gradient estimators are unbiased and independent of distributional information of supply and service processes involved. In addition, based on the fact that they can be evaluated using data from the observed actual (discrete event) system, we use them as approximate gradient estimators in simple iterative schemes for adjusting thresholds (hedging points) on line seeking to optimize an objective function that trades off throughput and buffer overflow costs.     

Multiobjective layout optimization of robotic cellular manufacturing systems

This paper proposes a multiobjective layout optimization method for the conceptual design of robot cellular manufacturing systems. Robot cellular manufacturing systems utilize one or more flexible robots which can carry out a large number of operations, and can conduct flexible assemble processes. The layout design stage of such manufacturing systems is especially important since fundamental performances of the manufacturing system under consideration are determined at this stage. In this paper, the design criteria for robot cellular manufacturing system layout designs are clarified, and objective functions are formulated. Next, layout design candidates are represented using a sequence-pair scheme to avoid interference between assembly system components, and the use of dummy components is proposed to represent layout areas where components are sparse. A multiobjective genetic algorithm is then used to obtain Pareto optimal solutions for the layout optimization problems. Finally, several numerical examples are provided to illustrate the effectiveness and usefulness of the proposed method.     

Industrial Additive Manufacturing: A manufacturing systems perspective

As Additive Manufacturing becomes increasingly prevalent in commercial manufacturing environments, the need to effectively consider optimal strategies for management is increased. At present most research has focused on individual machines, yet there is a wealth of evidence to suggest competitive manufacturing is best managed from a systems perspective. Through 14 case studies developed with four long-established Additive Manufacturing companies this paper explores the conduct of Industrial AM in contemporary manufacturing environments. A multitude of activities, mechanisms, and controls are identified through this detailed investigation of Additive Manufacturing operations. Based on these empirical results a general four component Industrial Additive Manufacturing System is developed, together with the identification of potential strategic opportunities to enhance future manufacturing.     

Multi-objective optimization of product variety and manufacturing complexity in mixed-model assembly systems

Product variety has increased dramatically as manufacturers compete for market shares. While higher variety of products may satisfy a broader range of customers, it also introduces complexity in manufacturing. A multi-objective optimization approach is proposed to balance product variety and manufacturing complexity when designing a product family and the mixed-model assembly system. Relative complexity is introduced to measure the complexity and to find the best set of product variants to be offered while balancing market share and complexity. Numerical examples are provided to demonstrate the approach.     

Designing cellular manufacturing systems under dynamic and uncertain conditions

The paper proposes a fuzzy programming based approach to design a cellular manufacturing system under dynamic and uncertain conditions. The dynamic condition indicates a multi-period planning horizon, in which the product mix and demand in each period can be different. As a result, the best cells designed for one period may not be efficient cells for subsequent periods and some of reconfigurations are required. Uncertain condition implicates to the imprecise nature of the part demand and also the availability of the manufacturing facilities in each period planning. An extended mixed-integer programming model of dynamic cellular manufacturing system, in which some of the coefficients in objective function and constraints are fuzzy quantities, is solved by a developed fuzzy programming based approach. The objective is to determine the optimal cell configuration in each period with maximum satisfaction degree of the fuzzy objective and constraint. To illustrate the behavior of the proposed model and verify the performance of the developed approach, a number of numerical examples are solved and the associated computational results are reported.     

A two phase optimization method for Petri net models of manufacturing systems

Optimization is a key issue in the design of large manufacturing systems. An adequate modeling formalism to express the intricate interleaving of competition and cooperation relationships is needed first. Moreover, robust and efficient optimization techniques are necessary. This paper presents an integrated tool for the automated optimization of DEDS, with application to manufacturing systems. After a very quick overview of optimization problems in manufacturing systems, it presents the integration of two existing tools for the modeling and evaluation with Petri nets and a general-purpose optimization package based on simulated annealing. The consideration of a cache and a two phase technique for optimization allows to speed-up the optimization by a factor of about 35. During the first preoptimization phase, a rough approximation of the optimal parameter set is computed based on performance bounds. Two application examples show the benefits of the proposed technique.     

Multi-agent approach and stochastic optimization: random events in manufacturing systems

We propose a method to solve industrial problems and to take into account random events. It is called the triple coupling. It is based on stochastic algorithms, a simulation model and the multi-agents model of artificial intelligence. The method we propose is easy to use and allows us to take into account most of the constraints found in manufacturing systems. Experts look for solutions to increasing the capacity of production. But the production can be disturbed by random events experienced by the system. Industrial experts need schedules which prevent the consequences of random events. Minimizing such consequences is very important to increasing system delivery. Capital investment is often very high in factories and the cost of the investment goes on regardless of whether the resources are running or not. The multi-agent approach is used to determine schedules for which the consequences of random events are low, and a stochastic algorithm is proposed which permits us to optimize a random variable. We prove that this algorithm finds, with probability one, the schedule of the production for which the consequences of random events are the lowest. We propose to measure the consequences of random events using an influence ratio. Our approach has been used to study the consequences of random events in Peugeot sand foundries of Sept-Fons (France). A benchmark test is presented to prove the efficiency of our solution. For the Peugeot sand foundry of Sept-Fond, random events increase the production time by about 20% compared with the production time without any random events occurring. We have determined schedules of production for which the consequences of random events are about 0.5%.     

Scalability planning for reconfigurable manufacturing systems

Scalability is a key characteristic of reconfigurable manufacturing systems, which allows system throughput capacity to be rapidly and cost-effectively adjusted to abrupt changes in market demand. This paper presents a scalability planning methodology for reconfigurable manufacturing systems that can incrementally scale the system capacity by reconfiguring an existing system. An optimization algorithm based on Genetic Algorithm is developed to determine the most economical way to reconfigure an existing system. Adding or removing machines to match the new throughput requirements and concurrently rebalancing the system for each configuration, accomplishes the system reconfiguration. The proposed approach is validated through a case study of a CNC-based automotive cylinder head machining system.     

A survey of flexible manufacturing systems

In this report, the different flexible manufacturing systems used for machining and assembling in the following countries are reviewed: the United States, Japan, the Federal Republic of Germany, the German Democratic Republic, Italy, Great Britain, Sweden, Norway, France, Czechoslovakia and Hungary.Three categories of systems discussed are (1) flexible modules and units, (2) flexible transfer lines, and (3) “unaligned” flexible systems. Within each category are several sub-groups, divided up mainly according to the conveyor system and operating mode. This classification shows the effective French position in this field.     

Coordinated scheduling of production and logistics for large-scale closed-loop manufacturing using Benders decomposition optimization

This paper studies coordinated scheduling of production and logistics for a large-scale closed-loop manufacturing system by integrating its manufacturing and recycling process. In addition to the forward manufacturing process, different recycling units in reverse recycling process are also studied. A decentralized network is designed to formulate the coordinated scheduling problem as a mixed integer programming model with both binary and integer variables. As the problem for closed-loop manufacturing is large-scale and computational-consuming in nature, the model is divided into integer variable sub-models and complex binary variable sub-models for preprocessing and reprocessing respectively. An iterative solution approach by Benders decomposition is developed to accelerate the solving efficiency in large-scale case by updating custom constraints. A case study is conducted to investigate the managerial implications of the decentralized network for the closed-loop manufacturing system. Computational experiments demonstrate the validity and efficiency of the proposed iterative solution approach for the large-scale scenarios.     

Phase change fixturing for flexible manufacturing systems

Fixturing is fundamental to many manufacturing operations, hence, if computer integrated flexible manufacturing systems are to be truly flexible, then the fixturing must also be flexible. That is, it must be capable of accomodating parts of different geometries and sizes. This paper reports on an innovative class of flexible fixtures which utilizes materials that undergo a phase change between solid and liquid states. When in the liquid state, the fixturing medium can accommodate a wide variety of different part geometries, while in the solid state the part is held fixed. A mathematical model is developed which governs the holding ability of a particular class of these fixtures and some results of parametric computer studies are then presented.     

Simulation and graphical animation of advanced manufacturing systems

Automated production systems, known as Flexible Manufacturing Systems (FMS), offer a promising solution for the low productivity of mid-volume, mid-variety batch production. These systems consist of integrated machine modules and material handling equipment under computer control.This paper describes a general purpose discrete-event Flexible Manufacturing Systems Simulator (FMSSIM). The package is programmed in FORTRAN and is capable of simulating different configurations, material handling systems, and topologies including bidirectional tracks. The simulator checks blockage of routes due to interference of carts and simulates random failures and repairs of the various components in the system. The simulator provides the user with a wide range of priority rules to select from, and enables the user to define his own rules if required. The simulator produces reports on various vital system performance statistics and also displays the movement of parts through the system on a refreshed CRT. This simulator is a modular, user-oriented package which allows the designer to evaluate a wide range of systems with varied design parameters and select an efficient flexible manufacturing system. Some general trends in the behaviour of the flexible manufacturing systems are identified and guidelines for their design and operation are suggested.     

Applications of queueing structures in manufacturing systems

This survey paper discusses and, to some extent, identifies manufacturing sub-systems that can be represented using accepted queueing models. Aggregate performance measures can be obtained through application of these models. Depending on the complexity of the congestion characteristics of the system, the standard results from queueing theory texts may yield guidelines for selection of optimal operational parameters.     

Technical investment planning of flexible manufacturing systems—The application of practice-oriented methods

Flexible manufacturing systems (FMS) exhibit a high degree of automation of the machining system and of the workpiece, and for the information flow systems. Therefore, these systems are amongst the most complex production installations and their technical investment planning must be undertaken with great care.This paper introduces a strategic planning procedure and describes auxiliary aids for the selection of the components and for structuring of the overall system. Computer programs for the selection of machine tools and for the simulation of the manufacturing process sequence are part of this procedure. The application of the methods is illustrated by means of several problem situations arising from industrial production companies; the examples show the practical usefulness of the developed auxiliary techniques. The planning accuracy possible by these methods reduces the investment risk associated with the use of these complex manufacturing systems.Also described is an integrated system for the technical investment planning of flexible manufacturing systems which comprises both existing methods and new auxiliary means for planning the machining systems and the technical/organizational overall concept.     

An object-oriented manufacturing control system

This paper presents the development of an event-driven control architecture and its implementation in a physical simulator of a computerized manufacturing system using object-oriented techniques. The architecture was developed to improve the efficiency of handling concurrent control events in the DOS environment. In the implementation, the control system of the physical simulator consists of four distinct layers of control devices: a PC/386 computer, a microcontroller, I/O modules and the system's control devices such as motors, solenoids and sensors. A control program residing in the PC/386 coordinates system-level tasks such as event scheduling, while a BASIC program running on the microcontroller handles all low-level control tasks such as sensor monitoring and motion control. The concepts and developments presented in this paper should help in implementing an efficient control system for both CIM systems and their physical simulators.     

Designing Holonic manufacturing systems

This paper discusses the design of Holonic manufacturing systems (HMS), with emphasis on manufacturing control. First, it discusses the concept of a Holonic system. Second, it presents the HMS reference architecture for manufacturing control. Third, it addresses the overall design problem, i.e. designing both the holonic control system and the underlying manufacturing system. Finally, the paper addresses the design and development of the control software itself.     

Requirements and languages for the semantic representation of manufacturing systems

In the last years, attention has been devoted to the development of ontologies, which are ICT conceptual models allowing a formal and shared representation of a particular domain of discourse, and to the use of these representations in a variety of contexts, among which also the industrial engineering can be counted. Within the industrial engineering field, the manufacturing domain has not yet seen a wide application of ontologies. This paper firstly shows the use of ontologies for the semantic annotation of a Web Service-based architecture for the control of manufacturing systems; and then contributes to the research field of manufacturing domain ontologies by proposing a thorough literature review and analysis of the available languages supporting such objective. The paper collects the main requirements that semantic languages must meet to be used in the manufacturing domain with the outlined purpose. In fact, the available semantic languages are several and characterized by different features: the paper identifies the most proper ones for the manufacturing domain representation thanks to their analysis against the main requirements. Lastly, the paper shows how the discussed topics are deployed in a real industrial example.     

Simulation of service-oriented and distributed manufacturing systems

In this paper modeling and simulation is discussed in the context of distributed manufacturing systems (DiMS). The DiMS concept aims towards efficient and innovative collaboration that integrates design and development activities of manufacturing systems. A DiMS, described formally as a digital manufacturing system, is a competent basis for the modeling and simulation of manufacturing systems. The activities of the simulation model are described on the basis of a service-oriented approach in which content of the services is completely known. Micro, meso, and macro manufacturing levels are applied to the modeling and simulation. By means of these levels the hierarchy of the communication of the services is illustrated. An example is described in which modeling and simulation is used to proceed from ideas to efficiently operated manufacturing systems.     

The evolving factory of the future: Integrating manufacturing and information systems

In recent years there have been rapid developments in both manufacturing and information technologies and their systems. Advances have occured so rapidly that often the results has been “islands” of automation and information subsystems, such as CAD/CAM, robotics, group technology, and office automation. Some recent developments, however, provide capabilities for integrating these “islands” into systems which both improve manufacturing productivity and produce more meaningful management information. Integrated systems seem imminent. Suggestions that could help ensure a smooth evolution toward these systems are made and some conclusions are drawn.