Reliability analysis of a flexible manufacturing cell

In this study, mathematical models are developed to study and compare the operations of a fully reliable and an unreliable flexible manufacturing cell (FMC), each with a flexible machine, a loading/unloading robot, and a pallet handling system. The operation times, loading/unloading times, and material handling times by the pallet are assumed to be random. The operation of the reliable cell is compared to that of an unreliable cell with respect to utilization of the cell components, including the machine, robot, and pallet handling system. The unreliable cell is assumed to operate under random (machine and robot) failures with constant failure rates for the machine and the robot. The pallet handling system is assumed to be completely reliable.     

The tool transporter movements problem in flexible manufacturing systems

We consider a job sequencing and tool transporter movements problem on a single flexible machine with limited tool magazine capacity. A tool transporter having limited capacity is used in transporting the tools between the machine and tool crib area. Our aim is to minimize the number of the tool transporter movements. We present several lower and upper bounds, propose a Branch-and-Bound algorithm and a Beam Search procedure, and report results from a computational experiment. We find that optimal solutions can be quickly obtained for medium-sized instances with 25 jobs and 25 tools. For large-sized problem instances, Beam Search provides high quality solutions very quickly. Finally, we address the problem of minimizing the total flow time.     

Loading and scheduling for flexible manufacturing systems with controllable processing times

This study addresses the problem of determining the allocation of operations and their tools to machines, the operation processing times and the allocation/sequence of the parts to be processed on each machine for flexible manufacturing systems with controllable processing times. Tool lives, tool copies and tool sharing are also considered. An integer programming model is developed for the objective of minimizing the sum of operation processing and tardiness costs. Then, iterative algorithms are proposed that solve the two subproblems iteratively, where the loading subproblem is solved by a modified bin packing algorithm under initial processing times and the resulting scheduling subproblem is solved by a priority scheduling method while modifying the loading plans and operation processing times iteratively. Computational experiments were carried out, and the results are reported.     

Activity-based costing in flexible manufacturing systems with a case study in a forging industry

The objective of this paper is to apply the activity-based costing (ABC) approach together with traditional costing (TC) for parts costing in flexible manufacturing systems (FMS) with the A(2) level of automation. We propose a new model for the implementation of ABC using the product cost tree concept. First, the required resources and activities for each part are recorded, and then their costs are calculated using the appropriate cost formulae. This model was applied in a forging industry. A comparison and analysis between ABC and TC was then carried out based on the computational results obtained from the case study. The results indicate that the ABC outputs are more reliable than the TC outputs, and thus the ABC approach is a more acceptable tool for parts costing in FMS.     

Mission reliability evaluation based on operational quality data for multistate manufacturing systems

Modern and intelligent manufacturing systems have a prominent multistate feature. However, previous studies of reliability analysis of multistate manufacturing systems mostly focused on the basic reliability of manufacturing systems but disregarded their operating characteristics, which has hindered the development of Prognostics and Health Management technique for intelligent manufacturing systems. Therefore, an evaluation approach of mission reliability for multistate manufacturing systems based on operational quality data is proposed in this paper. First, from the systematic viewpoint of the composition and operational principle of the manufacturing system, the relationship among production task execution state, production equipment degradation state, and produced product quality state is expounded, and the connotation of the mission reliability of multistate manufacturing systems is defined. Second, an extended state task network (ESTN) is presented to organise operational quality data by considering the quality state of work in process (WIP). Third, a fusion model of operational quality data for manufacturing systems is established with the aid of the ESTN, and an operational quality data-oriented evaluation method of mission reliability is been put forward. Finally, a case study of a manufacturing system for a cylinder head is conducted to verify the proposed approach.     

Optimal reliability and maintainability allocation in manufacturing systems

In this article an attempt has been made to solve an important task in the reliability management of manufacturing systems: the definition of reliability and maintainability specifications of parts, the general objective being to increase productivity while maintaining costs low. An analytical approach has been considered to evaluate an average index of production capability in series-parallel systems. A heuristic optimization procedure has been developed to solve the following problems: (a) determine the optimal reliability and maintainability allocation of parts to achieve the maximum production index at a given cost; and (b) determine the optimal reliability and maintainability allocation of parts which minimizes the total cost of investments, subject to the constraint of meeting a system production requirement. Numerical examples prove the effectiveness of the proposed procedure and show that the application of optimization analyses can provide large gains in terms of either productivity or total cost.     

A simulated annealing algorithm based on a closed loop layout for facility layout design in flexible manufacturing systems

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.     

A financial model of flexible manufacturing systems planning under uncertainty: identification,valuation and applications of real options

Flexible manufacturing systems (FMS) have been considered to be essential for manufacturers to succeed in the uncertain market place. Flexibility typically comes at a price and is only valuable as a hedge against environmental uncertainty. It is important to determine an appropriate level of flexibility in the production system while considering the tradeoffs between its costs and benefits. This paper proposes to apply a real option theoretic approach to the modeling and analysis of various types of uncertainty involved in an FMS's operational environment. In comparison with financial options, real options in the context of an FMS, namely, production options, are identified and accordingly a pricing model for production options is proposed based on the option theory. Based on the valuation of production options, a general framework of flexibility planning is formulated. The real option approach surmounts traditional discounted cash flow analysis based valuation methods that tend to ignore the upside potentials to an investment from management flexibility. The proposed model is tested in a refrigerator company that deals with high product variety and uncertain demand.     

Guidelines for implementing robust supervisors in flexible manufacturing systems

Over the past several years, researchers have developed numerous control policies that assure deadlock-free operation for flexible manufacturing systems. Using this research base as a foundation, we have developed several supervisory policies that assure robust operation in the face of resource failure. Along with deadlock-free operation, these policies guarantee that failure of unreliable resources does not block production of part types not requiring failed resources. In our previous work, we developed two types of robust policies, those that ‘absorb’ all parts requiring failed resources into the buffer space of failure-dependent resources (resources that support only parts requiring failed resources), and those that ‘distribute’ parts requiring failed resources among the buffer space of shared resources (resources shared by parts requiring and parts not requiring failed resources). These two types of robust controllers assure different levels of robust system operation and impose very different operating dynamics on the system, thus affecting system performance in different ways. In this research, we use extensive simulation and experimentation on a highly complex and configurable system to develop guidelines for choosing the best robust supervisor based on manufacturing system characteristics and performance objectives. We validate these guidelines using seven randomly generated complex systems and find a better than 88% agreement.     

Integrated analytical models for flexible manufacturing systems

Product form queueing networks (pfqn) and generalized stochastic Petri nets (gspn) have emerged as the principal performance modelling tools for flexible manufacturing systems (fms). In this paper, we present integratedpfqn-gspn models, which combine the computational efficiency ofpfqn and representational power ofgspn by employing the principle of flow-equivalence. We show thatfms that include nonproduct form characteristics such as dynamic routing and synchronization can be evaluated efficiently and accurately using the integrated models.     

Some reliability aspects in structural control

The reliability aspects associated with the system made of an actively controlled structure and its control devices are discussed. Standard tools of system reliability analysis turns out to be a convenient approach to the problem. The operation scenario however is preliminarily required and some redundancy solutions are discussed in this article.     

A genetic scheduling methodology for virtual cellular manufacturing systems: an industrial application

Effective solutions to the cell formation and the production scheduling problems are vital in the design of virtual cellular manufacturing systems (VCMSs). This paper presents a new mathematical model and a scheduling algorithm based on the techniques of genetic algorithms for solving such problems. The objectives are: (1) to minimize the total materials and components travelling distance incurred in manufacturing the products, and (2) to minimize the sum of the tardiness of all products. The proposed algorithm differs from the canonical genetic algorithms in that the populations of candidate solutions consist of individuals of different age groups, and that each individual's birth and survival rates are governed by predefined aging patterns. The condition governing the birth and survival rates is developed to ensure a stable search process. In addition, Markov Chain analysis is used to investigate the convergence properties of the genetic search process theoretically. The results obtained indicate that if the individual representing the best candidate solution obtained is maintained throughout the search process, the genetic search process converges to the global optimal solution exponentially.

The proposed methodology is applied to design the manufacturing system of a company in China producing component parts for internal combustion engines. The performance of the proposed age-based genetic algorithm is compared with that of the conventional genetic algorithm based on this industrial case. The results show that the methodology proposed in this paper provides a simple, effective and efficient method for solving the manufacturing cell formation and production scheduling problems for VCMSs.     

Application of the integrated reliability analysis system (IRAS)

This paper introduces a UNIX-based computer aided reliability assessment system, IRAS, which was developed in the Brite/Euram project BE-4250. It utilises fault propagation models for automatic generation of Fault Trees, Cause–Consequence Diagrams and FMECA. Therefore, it has the following features: a Model Builder which allows the creation of the fault propagation models in a hierarchical manner; a Fault Tree Analysis module that is able to generate Fault Trees on demand and to extract minimal cut sets; an FMECA module that is able to search for and group effects of basic events according to their criticality, severity and probability; a Real Time Fault Location (RTFL) module that enables the fast detection of the most probable cause(s) of system malfunction based on information available from sensors and/or operator. This paper describes the underlying ideas and procedures of IRAS and shows an example application to a Hot Strip Steel Mill.     

Virtual fusion: a hybrid environment for improved commissioning in manufacturing systems

Efficiency and quality are major factors contributing to profits in manufacturing systems. Production downtime occurs during commissioning of a new system, adoption of new processes, system faults, or (un)planned maintenance; all of which result in reduced production and profit loss. Current techniques for evaluating change to a manufacturing system rely on simulation and modeling to verify processes, but ignore the physical interactions of the work parts on the system. Implementation techniques to evaluate commissioning focus on identifying issues with the cyber interfaces, ignoring the physical interfaces. To validate the cyber and physical interfaces simultaneously, physical work are sent through the system, resulting in significant costs from scrapped work parts and loss of production time. This research proposes a virtual fusion environment where the physical interfaces between a virtual work part and a manufacturing system can be investigated in real-time, on the physical system, without the expenses associated with physical work parts. The virtual environment includes a virtual fusion filter to monitor discrepancies between the physical and virtual systems, and generate a hybrid virtual-physical input signal to the system level controller for virtualisation of a work part onto a physical system. Experimental demonstrations validate the feasibility of the proposed approach.     

Capacity allocation problem in flexible manufacturing systems: branch and bound based approaches

This study considers an operation assignment and capacity allocation problem that arises in flexible manufacturing systems. The machines have limited time and tool magazine capacities and the available tools are limited. Our objective is to maximise total weight of assigned operations. We develop a branch and bound algorithm that finds the optimal solutions and a beam search algorithm that finds high quality solutions in polynomial time.     

Service-based manufacturing systems: modelling and control

In service-based manufacturing systems, functionalities are independently developed as services and a central engine orchestrates their integration. As industrial processes tend to be very large, and performance and productivity are expected to be maximised, there is a constant interest in providing (in-advance) quality guarantees for services interactions, which contrasts with the usual non-automated workflow design. This paper provides an alternative to enhance service orchestration capabilities using supervisory control techniques. Initially, each component (atomic and composite activities) belonging to an orchestration language is modelled as a state-machine. Then, activity models are properly combined and composed, reproducing orchestrated workflows. Finally, supervisory control is used to calculate an optimal version of the orchestrator. Practical implications of handling large state-spaces are discussed and examples are provided.     

Markovian models for deadlock analysis in automated manufacturing systems

Deadlocks constitute a major issue in the desing and operation of discrete event systems. In automated manufacturing systems, deadlocks assume even greater importance in view of the automated operation. In this paper, we show that Markov chains with absorbing states provide a natural model of manufacturing systems with deadlocks. With illustrative examples, we show that performance indices such as mean time to deadlock and mean number of finished parts before deadlock can be efficiently computed in the modelling framework of Markov chains with absorbing states. We also show that the distribution of time to deadlock can be computed by conducting a transient analysis of the Markov chain model.