A heuristic algorithm for the loading problem in flexible manufacturing systems

The paper considers the loading problem in flexible manufacturing systems (FMSs). This problem involves the assignment to the machine tools of all operations and associated cutting tools required for part types that have been selected to be produced simultaneously. The loading problem is first formulated as a linear mixed 0–1 program with the objective to minimize the greatest workload assigned to each machine. A heuristic procedure is presented in which an assignment of operations to machine tools is obtained by solving a parameterized generalized assignment problem with an objective function that approximates the use of tool slots required by the operations assigned to the machines. The algorithm is coded in FORTRAN and tested on an IBM-compatible personal computer. Computational results are presented for different test problems to demonstrate the efficiency and effectiveness of the suggested procedure.     

Allocating buffer storages in a flexible manufacturing system

This article reports an approximation scheme to determine buffer capacities required to achieve the target performance level in a general flexible manufacturing system with multiple products. This work extends our previous study of sequential production lines with a single product. The manufacturing system is operated using a pull mechanism, and the performance level is measured by the average proportion of demands backlogged. Simulation experiments were performed to study the validity of the approximation scheme under various situations.     

Scheduling tasks and vehicles in a flexible manufacturing system

Due to their increasing applicability in modern industry, flexible manufacturing systems (FMSs), their design, and their control have been studied extensively in the recent literature. One of the most important issues that has arisen in this context is the FMS scheduling problem. This article is concerned with a new model of an FMS system, motivated by the practical application that takes into account both machine and vehicle scheduling. For the case of a given machine schedule, a simple polynomial-time algorithm is presented that checks the feasibility of a vehicle schedule and constructs it whenever one exists. Then a dynamic programming approach to construct optimal machine and vehicle schedules is proposed. This technique results in a pseudopolynomialtime algorithm for a fixed number of machines.     

利用已知血型血液鉴定未知血型血液的血型

在无标准A、B型血清的情况下,运用交叉配血的方法利用已知血型血液对未知血型血液进行血型鉴定。在分别将已知的O、B型血清与未知血型的血液混合,以及将未知血型血清与已知O、B型的血液混合,最终推测出3份血样的血型分别为B型、AB型和B型。     

An efficient heuristic for scheduling batches of parts in a flexible flow system

Flexible manufacturing systems (FMSs) are a class of automated systems that can be used to improve productivity in batch manufacturing. Four stages of decision making have been defined for an FMS—the design, planning, scheduling, and control stages. This research focuses on the planning stage, and specifically in the area of scheduling batches of parts through the system. The literature to date on the FMS planning stage has mostly focused on the machine grouping, tool loading, and parttype selection problems. Our research carries the literature a step further by addressing the problem of scheduling batches of parts. Due to the use of serial-access material-handling systems in many FMSs, the batch-scheduling problem is modeled for a flexible flow system (FFS). This model explicitly accounts for setup times between batches that are dependent on their processing sequence. A heuristic procedure is developed for this batch-scheduling problem—the Maximum Savings (MS) heuristic. The MS heuristic is based upon the savings in time associated with a particular sequence and selecting the one with the maximum savings. It uses a two-phase method, with the savings being calculated in phase I, while a branch-and-bound procedure is employed to seek the best heuristic solution in phase II. Extensive computational results are provided for a wide variety of problems. The results show that the MS heuristic provides good-quality solutions.     

A modular control design method for a flexible manufacturing cell including error handling

This paper introduces a new modular control design method for a cell controller with integrated error handling. To make the complexity of the cell controller manageable, its control logic is separated into two parts: resource allocation control and operation control. To create the operation control not only quickly but correctly, modular operation blocks integrated with error handling are developed. An algorithm automatically generates the operation control. The operation control created by the proposed method is proved to have desired control behaviors. The method is applied to an example system.     

A heuristic approach to handling missing data in biologics manufacturing databases

Bioprocess and Biosystems Engineering - The biologics sector has amassed a wealth of data in the past three decades, in line with the bioprocess development and manufacturing guidelines, and...     

An iterative approach to system setup problems in flexible manufacturing systems

System setup problems in flexible manufacturing systems deal with short-term planning problems such as part type selection, machine grouping, operation assignment, tooling, fixture and pallet allocation, and routing. In this article, we consider three of the subproblems: part type selection, machine grouping, and loading. We suggest a heuristic approach to solve the subproblems consistently with the objective of maximizing the expected production rate. The proposed procedure includes routines to generate all possible machine grouping alternatives for a given set of machines, to obtain optimal target workloads for each grouping alternative, and to allocate operations and tools to machine groups. These routines are executed iteratively until a good solution to the system setup problem is obtained. Computational experience is reported.     

A decision-making approach to the operation of flexible manufacturing systems

This paper introduces a generic decision-making framework for assigning resources of a manufacturing system to production tasks. Resources are broadly defined production units, such as machines, human operators, or material handling vehicles; and tasks are activities performed by resources. In the specific context of FMS, resources correspond to individual machines; tasks correspond to operations to be performed on parts. The framework assumes a hierarchical structure of the system and calls for the execution of four consecutive steps to make a decision for the assignment of a resource to a task. These steps are 1) establishment of decision-making criteria, 2) formation of alternative assignments, 3) estimation of the consequences of the assignments, and 4) selection of the best alternative assignment. This framework has been applied to an existing FMS as an operational policy that decides what task will be executed on which resource of this FMS. Simulation runs provide some initial results of the application of this policy. It is shown that the policy provides flexibility in terms of system performance and computational effort.     

A knowledge-based system for the strategic control level of robots in flexible manufacturing cells

The strategic control level synthesis for robots is related to a hierarchical robot control problem. The main control problem at the strategic control level is to select the model and algorithm to be used by the lower control level to execute the given robot task. Usually there are several lower control level models and algorithms that can be used by the robot control system for every robot task. Strategic control level synthesis depends on the particular robot system application. In a typical application, when the robot system is used in a flexible manufacturing system for manipulating various part types, the robot tasks executed by the robot system depend on the manufacturing processes in the system. If the robot system is applied in another flexible manufacturing system, dedicated to other manufacturing processes, another set of robot tasks might be needed to perform the necessary operations. Therefore, the quantity and the kind of knowledge required in the system for the strategic control level differ from one application to another. Such a fact creates the appropriate conditions for employing some artificial intelligence techniques. This article describes a knowledge-based system approach to the strategic control level synthesis problem.     

Dynamic load control policies for a flexible manufacturing system with stochastic processing rates

Real-time scheduling and load controls of FMSs are complex processes in which the control logic must consider a broad spectrum of instantaneous state variables while taking into account the probabilistic future impact of each decision at each time epoch. These processes are particularly important in the management of modern FMS environment, since they are known to have a significant impact on the FMS productive capacity and economic viability. In this article we outline the approach developed for dynamic load controls within an FMS producing a variety of glass lenses. Two revenue-influencing objective functions are evaluated for this capital-intensive facility. It is shown that by using Semi-Markovian modeling concepts, the FMS states need to be observed only at certain decision epochs. The mean holding time in each state is then obtained using the probability distribution function of the conditional state occupancy times. Several key performance measures are then derived by means of the value equations. In addition, the structure of the optimal policies are exemplified for a variety of operational parameters. It is shown that the optimal policies tend to generate higher buffer stocks of parts in those work centers having the highest revenue-generation rates. These buffer stocks get smaller and smaller as the relative processing capacity of the centers increases. Similar observations lead us to the introduction of several promising heuristics that capture the structural properties of the optimal policies with a significantly smaller computational effort. Results of the empirical evaluation of these heuristics are also analyzed here.     

A heuristic method to reconstruct the history of sequences subject to recombination

Summary Sequences subject to recombination and gene conversion defy phylogenetic analysis by traditional methods since their evolutionary history cannot be adequately summarized by a tree. This study investigates ways to describe their evolutionary history and proposes a method giving a partial reconstruction of this history. Multigene families, viruses, and alleles from within populations experience recombinations/gene conversions, so the questions studied here are relevant for a large body of data and the suggested solutions should be very practical. The method employed was implemented in a program, RecPars, written in C and was used to analyze nine retroviruses.     

Decision learning about production control as machines break down in a flexible manufacturing system

During manufacturing, there are many situations that can affect production performance. Such situations include machine breakdowns, rush orders, order changes, and order delays. When such issues occur, one has to make decisions to try to maintain production efficiency. Human decisions tend to be too late and incomplete in such contingencies. Thus a system that can make better decisions in time to maintain production performance is needed. To achieve this objective, the intelligent decision system described in this paper integrates artificial intelligence, an optimization technique, and simulation to solve such problems. The decision-making logic of the intelligent decision system is described by event graphs. It imitates the manner of human thinking. Self-learning of the decision-making process is used to strengthen the decision quality. In this study, a method of rule induction is applied to build up the self-learning system. There are two subsystems included in this system. One is rule generation and the other is knowledge management. A case for machine breakdowns is presented and discussed. A series of tests designed to validate the self-learning system are presented. These demonstrate that a rule induction method is suitable for constructing the self-learning.     

A rapid method to determine the mammalian cell cycle

A method was developed for determining the duration of the mammalian cell cycle and each of its major phases, mitosis, G1, DNA synthetic period, and G2. Mitotic time was determined by assessment of the mitotic index at intervals after cells collected in mitosis and stored at 4 °C were reincubated at 37 °C. The duration of the three remaining phases was derived from a graphic representation of the uptake of ³H-thymidine by a synchronous population of cells grown directly in scintillation vials. The scintillation counting method for determination of these parameters is advantageous over methods using autoradiography in that the investigator's bias in scoring cells is eliminated. Complex mathematical interpretations are unnecessary, and the data obtained from the scintillation counter are readily processed. Results from scintillation counting and autoradiographic methods are shown to be comparable.     

A theoretical experimental method to determine the locus of desensitization

Consider a ligand-gated channel with n agonist binding sites which can undergo desensitization. We present a theoretical experimental procedure for pinpointing the principal receptor state from which there is a transition to the desensitized state. The method is based on the observation that the dependence of the slope of the time constant of desensitization vs agonist concentration, at low concentrations, represents the state from which desensitization occurs. In those receptors where desensitization occurs from the open state (or the one immediately preceding it), the method also enables us to determine the number of binding sites.     

Quality control of an unreliable flexible manufacturing system with scrapping and infinite buffer capacity

Manufacturing multiple part types on a flexible manufacturing system (FMS) is increasingly becoming a rule rather than an exception. In such systems, attention has been drawn to the application of zero-defect technologies. However, in practice, this goal has remained elusive and costly. As a result, even though FMSs may be more reliable, producing fewer defective parts, system complexity and more stringent quality standards are rendering quality control in FMSs potentially useful. The goals of this article are threefold. First, we introduce a procedure for measuring and managing the in-process quality control of an FMS, which is described by an Open Queueing Network (OQN), bridging thereby a gap between queueing theory and quality control. Second, by focusing attention on the potential unreliabilities of FMSs, we provide some managerial insights regarding the role, position, and distribution of the quality control effort in an FMS. Finally, we stress the intricate relations between an FMS's operating characteristics and the manufactured quality and its control. Using numerical analyses, we draw some inferences regarding the design of such FMSs when both quality and quantity issues in the FMSs are considered. These simultaneous considerations of quantity and quality flows in an FMS have not been previously considered in the study of FMSs.     

A simple method to determine the enantiomeric ratio in enantioselective biocatalysis

The enantiomeric ratio (E) is commonly used to characterize the enantioselectivity in enzyme-catalyzed kinetic resolution. In this paper this parameter is directly derived from the enantiomeric excess of substrate and product. This is formally more correct than using Chen's equation after calculating the degree of conversion from both ee values using the relation of Sih and Wu. New expressions and useful graphs have been generated for reversible and irreversible uni-uni reactions. The theoretical predictions have been verified experimentally for various reactions. Values for E and the thermodynamic equilibrium constant,K_EQ, were obtained for a ( -dehalogenase-catalyzed dehalogenation, a hydrolysis reaction by porcine pancreatic lipase, and for C. Cylindracea lipase-catalyzed esterification and transesterification. In view of the current developments in the field of chiral analysis, this method is an easily available tool in the quantitative treatment of enzyme-catalyzed resolution of enantiomers.