Scheduling of FMSs with information delays: A simulation study

Practitioners and academicians throughout the world recognize the crucial role played by flexibility within manufacturing organizations, especially those engaged in small batch manufacture. However, although the concept of flexibility has begun to attract increased attention, its interaction with information integration and automation has not captured due attention. For example, it almost always has been assumed that a real-time control mechanism is available for exploiting routing flexibility on the shop floor. While this may be true for FMSs, it generally is not so for the vast majority of conventional manufacturing systems with varying levels of information integration and automation. The lack of a fully integrated and automated control mechanism within such semi-automated flexible manufacturing systems (SAFMSs) would eventually cause delays in the availability of shop status information. In this paper, we study the impact that defined modes of information delay have on the performance of a hypothetical SAFMS through detailed simulation experiments. Given that the level of routing flexibility is a controllable design parameter, our interest is in determining the impact that information delays have on decisions pertaining to the selection of appropriate levels of routing flexibility. To highlight the impact of information delays within the SAFMS, the Taguchi experimental design procedure is adopted as a performance evaluation and analysis vehicle, using makespan as a measure of performance. Simulation results indicate the presence of a system specific tolerance limit, operation below which minimizes performance loss.     

A fuzzy dispatching strategy for due-date scheduling of FMSs with information delays

Conventional dispatching strategies for FMSs with routing flexibility have typically employed simple heuristics such as work-in-next-queue (WINQ) and number-in-next-queue (NINQ). The effectiveness of these heuristics, however, deteriorates in FMSs whose operational environment must cope with information delays that are non-negligible in comparison to part processing times. Such delays could arise from planned activities, e.g., acquisition, selection, processing, and transfer of plant-wide system status information as well as from unplanned events such as ERP/IT system malfunctions, mismatch of software interfaces, and erroneous inventory master files, for example. Uncertainties from information delays make a strong case for the introduction of fuzzy controllers for making scheduling decisions. This paper introduces a novel fuzzy logic-based dispatching strategy to cope with a specific manifestation of information delays, called status review delay within FMSs. Status review information delays impact system performance adversely because of the obsolescent nature of the information used in the determination of dispatch decisions. A fuzzy dispatching strategy (FDS), designed specifically for deployment within FMSs where information delays are manifest, provides an appropriate alternative to conventional dispatching strategies such as WINQ and NINQ. In the design of an FDS, relevant system-based parameters are fuzzified and an appropriate rule base is designed. Simulation experiments demonstrate the superiority of an FDS over the conventional WINQ dispatching strategy using the mean tardiness, percent tardy, and mean flowtime performance measures.     

EVOLUTION OF GENETIC INTEGRATION BETWEEN DISPERSAL AND COLONIZATION ABILITY IN A BIRD

Discrete behavioral strategies comprise a suite of traits closely integrated in their expression with consistent natural selection for such coexpression leading to developmental and genetic integration of their components. However, behavioral traits are often also selected to respond rapidly to changing environments, which should both favor their context-dependent expression and inhibit evolution of genetic integration with other, less flexible traits. Here we use a multigeneration pedigree and long-term data on lifetime fitness to test whether behaviors comprising distinct dispersal strategies of western bluebirds—a species in which the propensity to disperse is functionally integrated with aggressive behavior—are genetically correlated. We further investigated whether selection favors flexibility in the expression of aggression in relation to current social context. We found a significant genetic correlation between aggression and dispersal that is concordant with consistent selection for coexpression of these behaviors. To a limited extent, individuals modified their aggression to match their mate; however, we found no fitness consequences on such adjustments. These results introduce a novel way of viewing behavioral strategies, where flexibility of behavior, while often aiding an organism's fit in its current environment, may be limited and thereby enable integration with less flexible traits.     

The Effects of Scheduling Rules and Routing Flexibility on the Performance of a Random Flexible Manufacturing System

The increased use of flexible manufacturing systems to efficiently provide customers with diversified products has created a significant set of operational challenges for managers. Many issues concerning procedures and policies for the day-to-day operation of these systems still are unresolved. Previous studies in this area have concentrated on various problems by isolating or simplifying the systems under study. The primary objective of this study is to extend previous research by examining the effects of scheduling rules and routing flexibility on the performance of a constrained, random flexible manufacturing system (FMS). Other experimental factors considered are shop load, shop configuration, and system breakdowns. Within the bounds of this experiment, the results indicate that, in the presence of total routing flexibility, the effects of shop load, system breakdowns, and scheduling rules are significantly dampened. In particular, when total routing flexibility exists, the choice of scheduling rules is not critical. We also show that the behavior of scheduling rules in a more constrained FMS environment (i.e., where system breakdowns occur and material handling capability is limited) is consistent with the findings of previous research conducted under less constrained environments. Finally, results indicate that the shop configuration factor has little or no impact on a system's flow-time performance.     

A Cascading Auction Protocol as a Framework for Integrating Process Planning and Heterarchical Shop Floor Control

A new contract net-style auction protocol is proposed as a framework for integrating process planning and shop floor control in heterarchical manufacturing systems. Process planning is partitioned into on-line and off-line activities; off-line process planning decisions are represented in a graph format and used as input for on-line process planning activities performed by machine controllers. Triggered by the opening round of an auction, the final on-line stages of process planning are dovetailed with the resource allocation process in the shop floor control system. The auction process allows final process planning decisions to be based on timely information, relying on the distribution of static process planning information rather than the distribution of a model of dynamic shop floor status and allowing a controller to identify all the primary and secondary resources and operations that must be provided for the incremental processing of a part.     

A pattern-directed approach to flexible manufacturing: A framework for intelligent scheduling,learning, and control

The planning, scheduling, and control of manufacturing systems can all be viewed as problem-solving activities. In flexible manufacturing systems (FMSs), the computer program carrying out these problem-solving activities must additionally be able to handle the shorter lead time, the flexibility of job routing, the multiprocessing environment, the dynamic changing states, and the versatility of machines. This article presents an artificial intelligence (AI) method to perform manufacturing problem solving. Since the method is driven by manufacturing scenarios represented by symbolic patterns, it is referred to as pattern-directed. The method is based on three AI techniques. The first is the pattern-directed inference technique to capture the dynamic nature of FMSs. The second is the nonlinear planning technique to construct schedules and assign resources. The third is the inductive learning method to generate the pattern-directed heuristics. This article focuses on solving the FMS scheduling problem. In addition, this article reports the computation results to evaluate the utility of various heuristic functions, to identify important design parameters, and to analyze the resulting computational performance in using the pattern-directed approach for manufacturing problem-solving tasks such as scheduling.     

Towards an Integration of Process Planning and Production Planning and Control for Flexible Manufacturing Systems

This introduction article attempts to present some major issues relating to the integration of process planning and production planning and control (PPC) for flexible manufacturing systems (FMSs). It shows that the performance of an FMS can be significantly improved and FMS capabilities more effectively utilized by integrating process planning and PPC functions. The various types of flexibility to be planned and provided for in process planning and manufacturing are summarized in the article, as well as emerging conceptual frameworks for integration, along with their implementation requirements and problems. Distinctive elements that differentiate these frameworks, such as the extent of integration of process planning and PPC activities, number of alternative process plans, and the time at which numerical control programs are generated, are discussed, followed by a brief summary of the articles compiled for this special issue.     

Effectiveness of flexible routing control

Flexibility in part process representation and in highly adaptive routing algorithms are two major sources for improvement in the control of flexible manufacturing systems (FMSs). This article reports the investigation of the impact of these two kinds of flexibilities on the performance of the system. We argue that, when feasible, the choices of operations and sequencing of the part process plans should be deferred until detailed knowledge about the real-time factory state is available. To test our ideas, a flexible routing control simulation system (FRCS) was constructed and a programming language for modeling FMS part process plans, control strategies, and environments of the FMS was designed and implemented. In addition, a scheme for implementing flexible process routing called data flow dispatching rule (DFDR) was derived. The simulation results indicate that flexible processing can reduce mean flow time while increasing system throughput and machine utilization. We observed that this form of flexibility makes automatic load balancing of the machines possible. On the other hand, it also makes the control and scheduling process more complicated and calls for new control algorithms.     

Performance management of manufacturing system networks

Performance management of communication networks is critical for speed, reliability, and flexibility of information exchange between different components, subsystems, and sectors (e.g., factory, engineering design, and administration) of production process organizations in the environment of computer integrated manufacturing (CIM). Essential to this distributed total manufacturing system is the integrated communications network over which the information leading to process interactions and plant management and control is exchanged. Such a network must be capable of handling heterogeneous traffic resulting from intermachine communications at the factory floor, CAD drawings, design specifications, and administrative information. The objective is to improve the efficiency in handling various types of messages, e.g., control signals, sensor data, and production orders, by on-line adjustment of the parameters of the network protocol. This paper presents a conceptual design, development, and implementation of a network performance management scheme for CIM applications including flexible manufacturing. The performance management algorithm is formulated using the concepts of: (1) Perturbation analysis of discrete event dynamic systems; (2) stochastic approximation; and (3) learning automata. The proposed concept for performance management can also serve as a general framework to assist design, operation, and management of flexible manufacturing systems. The performance management procedure has been tested via emulation on a network test bed that is based on the manufacturing automation protocol (MAP) which has been widely used for CIM networking. The conceptual design presented in this paper offers a step forward to bridging the gap between management standards and users' demands for efficient network operations since most standards such as ISO and IEEE address only the architecture, services, and interfaces for network management.     

An approach to real-time flexible scheduling

Two types of flexibility are important in manufacturing scheduling in general and in real-time scheduling in particular. The first is flexibility with respect to the criteria that can be considered in the scheduling decisions. The second is flexibility with respect to the trade-off between decision quality and computational burden: that is, the ability to arrive at a solution that makes maximum use of theavailable computational capacity and computation time. This paper describes a procedure which meets the above requirements. The procedure is justified using a theoretical analysis based on probability. Experimental results of the procedure's performance are also presented. The results show that random selection (which is used in the procedure) can play a useful role in the real-time scheduling problem.     

Time delays in metabolic control systems

In this work we use mathematical models with discrete and distributed time delays to analyse the stability of metabolic pathways controlled by end product. We assume the kinetics of the intermediates of the path to be unknown, and we cover the lack of information by using a time delay. We find that above a definite substrate value, there is a critical delay Tc in which a transition from stability to instability occurs. For discrete delays, we find that even if the interaction of the end product with the first (allosteric) enzyme is not cooperative, the pathway can potentially become unstable and oscillate. We then show that the existence of cooperative inhibition extends the parametric domain of instability. The introduction of distributed delays shows, when the kernels are not monotonically decreasing, that the dispersion increases the critical delay Tc. Finally, we comment on the possibility that metabolic oscillations are physiological signals useful for triggering adaptive strategies in cell behavior.     

SBEAMS-Microarray: database software supporting genomic expression analyses for systems biology

Background  

The biological information in genomic expression data can be understood, and computationally extracted, in the context of systems of interacting molecules. The automation of this information extraction requires high throughput management and analysis of genomic expression data, and integration of these data with other data types.     

Economics and success factors of flexible manufacturing systems: The conventional explanation revisited

This article analyzes costs and relative benefits of several hundred flexible manufacturing systems (FMSs) in the world. The analyses are based on the computerized data bases, which make it easy to correlate different cost and benefit indicators with each other and to look for regular patterns and tendencies in the applications. Both investment cost distributions and the system complexity distributions are analyzed. The relative benefits and advantages and their relationships are shown. Finally, technical and economic explanations for successful implementation strategies are given. The results show that there are two classes of economically successful systems. The small-scale and technically compact systems are usually used in small-batch production for the replacement of semimanual production. The main benefits are increased capacity and productivity as well as quality improvements. The large-scale and technically complex systems are used in large-volume production for the replacement of fixed automation and transfer lines. The benefits are mainly due to the increased potential for flexibility and capital savings.     

A neural systems analysis of adaptive navigation

In the field of the neurobiology of learning, significant emphasis has been placed on understanding neural plasticity within a single structure (or synapse type) as it relates to a particular type of learning mediated by a particular brain area. To appreciate fully the breadth of the plasticity responsible for complex learning phenomena, it is imperative that we also examine the neural mechanisms of the behavioral instantiation of learned information, how motivational systems interact, and how past memories affect the learning process. To address this issue, we describe a model of complex learning (rodent adaptive navigation) that could be used to study dynamically interactive neural systems. Adaptive navigation depends on the efficient integration of external and internal sensory information with motivational systems to arrive at the most effective cognitive and/or behavioral strategies. We present evidence consistent with the view that during navigation: 1) the limbic thalamus and limbic cortex is primarily responsible for the integration of current and expected sensory information, 2) the hippocampal-septal-hypothalamic system provides a mechanism whereby motivational perspectives bias sensory processing, and 3) the amygdala-prefrontal-striatal circuit allows animals to evaluate the expected reinforcement consequences of context-dependent behavioral responses. Although much remains to be determined regarding the nature of the interactions among neural systems, new insights have emerged regarding the mechanisms that underlie flexible and adaptive behavioral responses.     

Production activity control: A practical approach to scheduling

There is a widely perceived gap within the domain of scheduling for manufacturing systems, namely, many of the methods employed by production supervisors are quite different from those developed by researchers. In a sense, this inconsistency highlights the important fact that much scheduling research has failed to win approval where it matters most, namely, within the manufacturing system. In this article, we argue for a practical approach to scheduling for manufacturing systems, one that we believe can narrow, and possibly bridge, the gap between theory and practice. This approach is based upon a well-defined and modular architecture for scheduling, termedproduction activity control. This architecture is the foundation of our proposed solution to scheduling, since it provides a coherent blueprint for the synthesis of information technology and scheduling strategies. The result of this synthesis is a design tool for production activity control, which allows for detailed and disciplined experimentation with a range of scheduling strategies in a controlled and simulated environment. Due to the unique modular property of the design tool, these strategies may then be implemented live in a flexible manufacturing facility, hence narrowing the gap between scheduling theory and manufacturing practice. Our overall approach is tested through an appropriate implementation in a modern electronics assembly plant.     

Neural network modeling for on-line estimation of nutrient dynamics in a sequentially-operated batch reactor.

In monitoring and controlling wastewater treatment processes, on-line information of nutrient dynamics is very important. However, these variables are determined with a significant time delay. Although the final effluent quality can be analyzed after this delay, it is often too late to make proper adjustments. In this paper, a neural network approach, a software sensor, was proposed to overcome this problem. Software sensor refers to a modeling approach inferring hard-to-measure process variables from other on-line measurable process variables. A bench-scale sequentially-operated batch reactor (SBR) used for advanced wastewater treatment (BOD plus nutrient removal) was employed to develop the neural network model. In order to improve the network performance, the structure of neural network was arranged in such a way of reflecting the change of operational conditions within a cycle. Real-time estimation of PO3-(4), NO-3, and NH+4 concentrations was successfully carried out with the on-line information of the SBR system only.     

Dynamic Excitatory and Inhibitory Gain Modulation Can Produce Flexible,Robust and Optimal Decision-making

Behavioural and neurophysiological studies in primates have increasingly shown the involvement of urgency signals during the temporal integration of sensory evidence in perceptual decision-making. Neuronal correlates of such signals have been found in the parietal cortex, and in separate studies, demonstrated attention-induced gain modulation of both excitatory and inhibitory neurons. Although previous computational models of decision-making have incorporated gain modulation, their abstract forms do not permit an understanding of the contribution of inhibitory gain modulation. Thus, the effects of co-modulating both excitatory and inhibitory neuronal gains on decision-making dynamics and behavioural performance remain unclear. In this work, we incorporate time-dependent co-modulation of the gains of both excitatory and inhibitory neurons into our previous biologically based decision circuit model. We base our computational study in the context of two classic motion-discrimination tasks performed in animals. Our model shows that by simultaneously increasing the gains of both excitatory and inhibitory neurons, a variety of the observed dynamic neuronal firing activities can be replicated. In particular, the model can exhibit winner-take-all decision-making behaviour with higher firing rates and within a significantly more robust model parameter range. It also exhibits short-tailed reaction time distributions even when operating near a dynamical bifurcation point. The model further shows that neuronal gain modulation can compensate for weaker recurrent excitation in a decision neural circuit, and support decision formation and storage. Higher neuronal gain is also suggested in the more cognitively demanding reaction time than in the fixed delay version of the task. Using the exact temporal delays from the animal experiments, fast recruitment of gain co-modulation is shown to maximize reward rate, with a timescale that is surprisingly near the experimentally fitted value. Our work provides insights into the simultaneous and rapid modulation of excitatory and inhibitory neuronal gains, which enables flexible, robust, and optimal decision-making.     

Flexibility in manufacturing and services: achievements, insights and challenges

The concept of flexibility has attracted considerable interest in the last 25 years in the context of manufacturing. This paper develops a framework for thinking about flexibility in the context of making decisions about the design and operation of systems in either manufacturing or service environments. Three different aspects of flexibility are defined: prior flexibility, state flexibility and action flexibility, and the issues in the measurement of flexibility are discussed. The use of flexibility ideas by industry in manufacturing and services is reviewed and key contributions to the academic literature are summarized. Major issues and insights arising from a focus on flexibility are discussed. The paper concludes with some challenges for future research.     

Flexible oviposition strategies in túngara frogs and their implications for tadpole spatial distributions

Because oviposition site selection is often studied in a single ecological context, little is known about flexibility in oviposition strategies. We studied the oviposition site selection strategies of túngara frogs ( Physalaemus pustulosus ) with respect to conspecific eggs and larvae in two different ecological contexts-arrays of artificial ponds and natural stream pools. We fit maximum likelihood models to sequential pond use data for both systems and found that strategies for oviposition differed greatly between the two systems. Within arrays of artificial ponds, túngara frogs avoided both conspecific egg masses and conspecific larvae. However, within a set of natural stream pools, túngara frogs consistently oviposited in the same pools from night to night, while many nearby ponds went unused. These variable strategies produced very different distributions of tadpoles among ponds, such that tadpoles tended to be evenly spread among artificial ponds, but highly clumped within stream pools. The difference between the two strategies appears to be an overriding effect of habitat quality. Surface area and the amount of leaf litter were all significant predictors of whether stream pools were used. Additionally, an experiment in which egg masses were either transplanted to, or removed from, selected stream pools provided no evidence that frogs in these pools used egg masses per se as a cue for oviposition. These results illustrate that oviposition strategies may be very flexible, allowing species to adjust strategies to different ecological contexts. Furthermore, they demonstrate that variation in oviposition strategies may have strong effects on egg and larval spatial distributions in patchy environments.     

Moving targets: collective decisions and flexible choices in house-hunting ants

Many decisions involve a trade-off between commitment and flexibility. We show here that the collective decisions ants make over new nest sites are sometimes sufficiently flexible that the ants can change targets even after an emigration has begun. Our findings suggest that, in this context, the ants’ procedures are such that they can sometimes avoid ‘negative information cascades’ which might lock them into a poor choice. The ants are more responsive to belated good news of a higher quality nest than they are when the nest they had initially chosen degraded to become worse than an alternative. Our study confirms, in a new way, that ant colonies can be very powerful “search engines”.