A comparative study of FMS tool allocation and part type selection approaches for a varying part type mix

Hankins and Rovito (1984) examined the impact of different tool policies on cutting tool inventory levels and spindle utilization for a flexible manufacturing system (FMS). This study provides a broader perspective of the impact of tool allocation approaches on flow times, tardiness, percent of orders tardy, machine utilization, and robot utilization. Part type selection procedures have been suggested for the FMS prerelease planning problem. However, very little research has specifically evaluated the part type selection procedures across different tool allocation approaches. Also, with the exception of Stecke and Kim (1988, 1991) no other known study has provided any insights on what tool allocation approaches are appropriate when processing different mixes of part types. This research is devoted to addressing those issues. Three tool allocation approaches, three production scheduling rules, and three levels of part mix are evaluated in this study through a similation model of a flexible manufacturing system. The specific impacts of the tool approaches, their interaction effects with the part type selection rules, and their effectiveness at different part type mix levels are provided through the use of a regression metamodel.     

An analytical representation of flexible resource allocation in hospitals

Non-linear processes within complex systems are difficult to predict. Using discrete event simulation (DES) models can be helpful for presenting the uncertainty level embedded within these processes. However, the interpretations of the resulting outcomes can be challenging to analyze. This is evident when experimenting with simulation models, and therefore requires the adaptation of existing models. Introducing cyclic entities such as interconnected resources to the simulation model adds a new level of complexity to the model. In practical cases, decision makers often demand a model that enables them to make quick decisions with less complexity involved. However, these individuals still want to be assured of a high degree of accuracy in the results. This article demonstrates how an analytical representation of complex DES models can be developed in order to facilitate prompt yet effective solutions for decision makers. This analytical representation provides a brief overview of the simulation results by using the staff scheduling and nurses’ utilization approaches. Results of the effective use of DES model and managers feedback are encouraging.     

Analysis of flexibility with rationing for a mix of manufacturing facilities

A major competitive advantage of a flexible manufacturing facility is its ability to cope with uncertainties in demand. At a strategic level, capacity-size decisions for a mix of flexible facilities (each not necessarily producing the same combination of products) are made based on aggregates of product types. Such an approach overlooks possible capacity-devouring by some products, arising at the operational level, when the aggregate demand for the period exceeds the available capacity. A rationing policy is required to ensure that the available aggregate capacity of the facilities is shared equitably. In this article, it is shown that such a rationing policy has an impact on the required capacity size and, therefore, must be integrated with the decisions at the strategic level. Several properties indicating the relative preferences of certain facility strategies are also established.     

Scheduling data analytics work with performance guarantees: queuing and machine learning models in synergy

In today’s scaled out systems, co-scheduling data analytics work with high priority user workloads is common as it utilizes better the vast hardware availability. User workloads are dominated by periodic patterns, with alternating periods of high and low utilization, creating promising conditions to schedule data analytics work during low activity periods. To this end, we show the effectiveness of machine learning models in accurately predicting user workload intensities, essentially by suggesting the most opportune time to co-schedule data analytics work. Yet, machine learning models cannot predict the effects of performance interference when co-scheduling is employed, as this constitutes a “new” observation. Specifically, in tiered storage systems, their hierarchical design makes performance interference even more complex, thus accurate performance prediction is more challenging. Here, we quantify the unknown performance effects of workload co-scheduling by enhancing machine learning models with queuing theory ones to develop a hybrid approach that can accurately predict performance and guide scheduling decisions in a tiered storage system. Using traces from commercial systems we illustrate that queuing theory and machine learning models can be used in synergy to surpass their respective weaknesses and deliver robust co-scheduling solutions that achieve high performance.     

Integrated scheduling of elective surgeries and surgical nurses for operating room suites

Facing an acute shortage of surgical nurses, operating room suites in China are more and more aware of the need to use surgical nurses efficiently. This goal is hard to achieve due to the strong interactions between the nurse and the surgery scheduling process. This paper addresses the benefit of integrating elective surgery and surgical nurse scheduling in terms of nurse utilization. First, an integer programming (IP) model is proposed to schedule elective surgeries and surgical nurses simultaneously. Then an efficient genetic algorithm (GA) is proposed based on the IP formulation due to the computational complexity of the integrated scheduling problem. A case study using real-life data is presented to validate the performance of the integrated approaches (the IP model and the GA) by comparing them with a two-stage approach that schedules elective surgeries and surgical nurses sequentially.     

On the controllability of continuous fermentation processes

Simulation may be used as a powerful tool for accelerating bioprocess design. This paper demonstrates the use of simulations in exploring the nature and impact of the interactions that exist in a typical bioprocess for the recovery of an intracellular protein. The study shows that an integrated approach to design must be adopted in order to achieve acceptable process designs. Data from a fed-batch fermentation, with verified models for cell harvesting, cell disruption and cell debris removal have been integrated to demonstrate the consequence of process design and operating decisions on the resulting process performance. The trade-offs between product recovery and the extent of cell debris removal for a range of operating conditions have been represented through a series of windows of operation which show how process conditions must be altered in order for given process performance levels to be realised. The capacity to account for process performance including the impact of interactions is seen as a pre-requisite for rigorous bioprocess sequence design and optimisation.     

Vehicle dispatching for highly loaded semiconductor production considering bottleneck machines first

Semiconductor wafer fabrication lines can be characterized by re-entrant product flow, long production lead-time, large variety of production processes, and large capital investment. These distinctive characteristics make the flow control in the fab very complicated. Throughput rate and lead-time are among the most important performance measures. The throughput rate is usually determined by a bottleneck resource, and the lead-time depends on the machine utilization level and the amount of variability in the system. Due to the high efficiency of material handling and reduced particles, automated material handling systems such as automatic guided vehicles (AGVs), overhead hoist transporters (OHTs), and overhead shuttles (OHSs) are being widely used in wafer fabrication lines (wafer fabs) instead of human operators. Although a material handling system itself is seldom a bottleneck of production in a fab, it is important for that to effectively support the bottleneck machines to maximize the throughput and reduce production lead-time. This paper presents a vehicle dispatching procedure based on the concept of theory of constraints, in which vehicle dispatching decisions are made to utilize the bottleneck machines at the maximum level. Simulation experiments have been performed to compare the proposed vehicle dispatching procedure with existing ones under different levels of machine utilization, vehicle utilization, and local buffer capacity.     

On the Consequences of Information Delays in the Scheduling of Semi-Automated Flexible Machines

Manufacturing systems with varying levels and types of flexibility employ alternative scheduling strategies to exploit flexibility for performance enhancement. Scheduling decisions in manufacturing systems are influenced by time delays due to information handling activities such as information collection, transfer, and processing. More specifically, scheduling strategies implicitly involve information intensive activities that may entail significant time delays for implementation, depending on the extant shop floor automation and integration within a flexible system. These are information delays and we believe that most contemporary flexible systems must inherently cope with some level of information delay when implementing on-line scheduling strategies. This paper conceptualizes the manifestation of information delays in the context of scheduling decisions within flexible systems through the definition of three key delay modes: (i) Mode 1 information-transfer delay; (ii) Mode 2 decision-implementation delay; and (iii) Mode 3 status-review delay. We then stress the need and importance of devising suitable on-line scheduling strategies for countering the effect of information delays by demonstrating the efficacy of a novel scheduling strategy on a single machine. While opening a new scheduling dimension with potential research ramifications, this paper highlights the fact that the concept of information delay can effectively capture the synergism issues related with flexibility, integration, and automation in the context of scheduling decisions within semi-automated flexible systems.     

Analysis of flexible manufacturing systems with distinct repeated visits: DrQ

This article examines the performance effects caused by repeated part visits at the workstations of a flexible manufacturing system (FMS). Such repeated part visits to the same workstations are commonly associated with fixture changes for machining complex parts, reclamping, and remounting or reorienting them. Since each of the repeated visits to a workstation may require different processing requirements, the resulting queueing network does not have a product form solution. We therefore develop an approximate mean value analysis model for performance evaluation of an FMS that may produce multiple part types with distinct repeated visits. We provide numerical examples and validate the accuracy of our solution algorithm against simulation. These examples show that the proposed model produces accurate throughput and utilization predictions with minimal computational efforts. These examples reveal that increasing the total pallet population may result in a reduction of the aggregate throughput, and that the FMS's performance could be more sensitive to the mix of pallets and part routes than to the total number of pallets. Our model will be of use, in particular, when managers wish to control individual operations (e.g., to adjust individual operation times to achieve economic savings in tool wear and breakage costs) or to investigate the performance implications of route changes due to alternate assignments of particular manufacturing tasks to certain workstations.     

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.     

How can the social sciences work with ecology in informing feral horse policy and management in south‐eastern Australia?

Feral horse management is a complex social issue. Committed and active stakeholders hold strong beliefs regarding both the level of culling needed and humane approaches to control. Ecological evidence supporting control and expert advice on ethical culling can, in such contexts, have limited effect in policy development and application. Given this complexity, social scientists have an important role to play in developing longer term solutions. Three possible approaches are evident: the use of knowledge exchange and boundary spanning expertise; the proactive development of publicly available evidence‐informed narratives; and the development of influence and leadership at the science–policy interface. Social scientists, ecologists, managers and policymakers need to work together to develop and implement sound management decisions.     

A cost-benefit analysis of using cloud computing to extend the capacity of clusters

In this paper, we investigate the benefits that organisations can reap by using “Cloud Computing” providers to augment the computing capacity of their local infrastructure. We evaluate the cost of seven scheduling strategies used by an organisation that operates a cluster managed by virtual machine technology and seeks to utilise resources from a remote Infrastructure as a Service (IaaS) provider to reduce the response time of its user requests. Requests for virtual machines are submitted to the organisation’s cluster, but additional virtual machines are instantiated in the remote provider and added to the local cluster when there are insufficient resources to serve the users’ requests. Naïve scheduling strategies can have a great impact on the amount paid by the organisation for using the remote resources, potentially increasing the overall cost with the use of IaaS. Therefore, in this work we investigate seven scheduling strategies that consider the use of resources from the “Cloud”, to understand how these strategies achieve a balance between performance and usage cost, and how much they improve the requests’ response times.     

Developing manufacturing control software: A survey and critique

The complexity and diversity of manufacturing software and the need to adapt this software to the frequent changes in the production requirements necessitate the use of a systematic approach to developing this software. The software life-cycle model (Royce, 1970) that consists of specifying the requirements of a software system, designing, implementing, testing, and evolving this software can be followed when developing large portions of manufacturing software. However, the presence of hardware devices in these systems and the high costs of acquiring and operating hardware devices further complicate the manufacturing software development process and require that the functionality of this software be extended to incorporate simulation and prototyping. This paper reviews recent methods for planning, scheduling, simulating, and monitoring the operation of manufacturing systems. A synopsis of the approaches to designing and implementing the real-time control software of these systems is presented. It is concluded that current methodologies support, in a very restricted sense, these planning, scheduling, and monitoring activities, and that enhanced performance can be achieved via an integrated approach.     

A collaborative approach to bridging the gap between wildlife managers and researchers

Although most wildlife professionals agree that science should inform wildlife management decisions, disconnect still exists between researchers and managers. If researchers are not striving to incorporate their findings into management decisions, support for research programs by managers can wane. If managers are not using research findings to inform management decisions, those decisions may be less effective or more vulnerable to legal challenges. Both of these situations can have negative consequences for wildlife conservation. We outline a collaborative research-management approach to bridging the gap between wildlife managers and researchers. We describe differences in perspectives, perceptions, and priorities between managers and researchers; outline how and why the divide between researchers and managers has likely occurred and continues to grow; and present specific strategies and recommendations to foster stronger collaborations between managers and researchers. We advocate increased synergy between managers and researchers based on a shared vision of conservation and a collaborative structure that rewards researchers and managers. Most importantly, we suggest that relationships and communication between managers and researchers must be established early in research development and decision-making processes, fostering the trust needed for collaboration. Institutions and agencies can facilitate these relationships by creating opportunities and incentives for integrating collaborative research into management decisions. We suggest this approach will strengthen ties between researchers and managers, increase relevance of research to management decisions, promote effectiveness of management decisions, reduce legal challenges, and ultimately produce positive, tangible, and lasting effects on wildlife conservation. © 2019 The Wildlife Society.     

Cyberinfrastructure for sourcing and processing ecological data

Cyberinfrastructure is a product of the information age that provides a framework for informing adaptive management of ecological entities under the impact of regional and global change. It supports proximity monitoring, user-friendly data management, knowledge discovery by data synthesis, and decision making by forecasting.A workflow is proposed that suits the iterative nature of adaptive management. It takes advantage of novel sensor, genomics, and communication technology for ecological monitoring, of ontologies, semantic webs and blockchain for data management, of hybrid, machine and deep learning concepts for data synthesis and forecasting. Forecasting at different time horizons is guiding decision making for adjusting management and continuing monitoring.This review aims to make researchers, decision makers and stakeholders aware of currently existing technology to make better use of ecological data and models for timely and evidence-based decisions.     

Flexibility analysis of a surface mount technology electronic assembly plant: An integrated model using simulation

This paper focuses on developing an integrated model using simulation to evaluate the effect of several independent variables on the performance of a surface mount technology (SMT) production line. Real data and an existing SMT line from a high product mix/low volume electronics manufacturer are used to conduct the analysis. The independent variables used are set-up formation policies (group technology based family grouping methods), machine feeder types, similarity factor in set-up formation, parts reduction at design step of products, and inter-families and intra-family scheduling rules. In addition, a new method of grouping products is proposed. The measures of performance evaluated by the model are average lead time, average work-in-process (WIP) inventory and average set-up time. Data analysis shows that the proposed method of grouping products will reduce set-up time and lead time while slightly increasing WIP. The proposed simulation model helps assess the effects of some of the independent variables on line performance. Recommendations are made in order to help the user choose the best alternative to improve production line productivity and flexibility.     

What Sources Are Natural Resource Managers Using to Make Decisions?

Natural resource management is more effective when it includes collaboration among numerous stakeholders who bring multiple perspectives to the decision-making process. In particular, many individuals and organizations (e.g., The Wildlife Society) have advocated for decisions to be science-based as a means for improving management outcomes. But there has been little research evaluating the sources, science-based or otherwise, used by natural resource agencies to support decision-making at the state-level within the United States. We surveyed state natural resource agency personnel in all 50 states to assess the sources of information used to make management decisions and the factors that influenced selection of the sources. Approximately 60% of respondents reported using ≥3 different source types when making recommendations. Existing management plans, the peer-reviewed scientific literature, and expert opinion were the most frequently used sources. Perception of source relevance was the most frequent predictor of source use, and the number of management plans a manager had previously written positively predicted the use of management plans, expert opinion, and personal experiences. Ninety percent of respondents reported that increased use of the peer-reviewed literature would or might improve management recommendations. Aspects of academic and agency cultures influenced which articles or journals were used to make recommendations. Our findings indicate managers support the use of peer-reviewed literature as an important component of management decision-making; however, if the goal is to improve the flow of information between scientists and managers, researchers should publish in journals that are readily accessible to managers and present results in a way that clearly articulates relevance to management decisions. © 2021 The Wildlife Society.     

Facing complexity in tropical conservation: how reduced impact logging and climatic extremes affect beta diversity in tropical amphibian assemblages

Biodiversity in pristine forest biomes is increasingly disturbed by human activity. Drivers such as logging and climate extremes are thought to collectively erode diversity, but their interactions are not well understood. However, ignoring such complexities may result in poor conservation management decisions. Here, we present the first study dealing with the complexity arising from the effects of interactions of two increasingly important disturbance factors (selective logging and climatic extreme events) on beta diversity patterns at different scales. Specifically, we examined extensive amphibian assemblage datasets obtained within a quasi‐experimental pre‐/post‐harvesting scheme in the lowland rainforests of Central Guyana. Changes in small‐scale patterns of beta diversity were not detectable at the higher landscape level, indicating that local‐scale dynamics are more informative for evaluating disturbance impacts. The results also underscore the importance of including abundance data when investigating homogenization or heterogenization effects, which should be considered when designing post‐logging impact assessments and selecting impact indicators. Moreover, logging should be regarded as a multifaceted driver that contributes to changes in biodiversity patterns in different ways, depending on interactions with other drivers. The effects of extreme climate events were significantly more pronounced in unlogged forest, while logged forest assemblages appeared buffered due to the presence of novel habitats. Imprudent post‐logging renaturation measures may thus counteract conservation targets. These findings highlight the fact that indicator bias and unaccounted interactions between multiple drivers can lead to misguided management strategies.     

A management-oriented framework for selecting metrics used to assess habitat- and path-specific quality in spatially structured populations

Mobile species with complex spatial dynamics can be difficult to manage because their population distributions vary across space and time, and because the consequences of managing particular habitats are uncertain when evaluated at the level of the entire population. Metrics to assess the importance of habitats and pathways connecting habitats in a network are necessary to guide a variety of management decisions. Given the many metrics developed for spatially structured models, it can be challenging to select the most appropriate one for a particular decision. To guide the management of spatially structured populations, we define three classes of metrics describing habitat and pathway quality based on their data requirements (graph-based, occupancy-based, and demographic-based metrics) and synopsize the ecological literature relating to these classes. Applying the first steps of a formal decision-making approach (problem framing, objectives, and management actions), we assess the utility of metrics for particular types of management decisions. Our framework can help managers with problem framing, choosing metrics of habitat and pathway quality, and to elucidate the data needs for a particular metric. Our goal is to help managers to narrow the range of suitable metrics for a management project, and aid in decision-making to make the best use of limited resources.     

RELIABILITY OF SENSORY ASSESSORS: ISSUES OF COMPLEXITY

The objective of this study was to investigate whether the sensory performance of assessors in a sensory panel maybe explained by complexity of evaluated product. We aimed to investigate whether we could observe a decline in sensory performance when increasing the complexity of the product. The products increased in number of constituents from mixtures of sucrose, sodium chloride, citric acid and caffeine in water, to the foods ice tea and tomato soup constituting different levels of the same substances. Candidates who succeeded evaluating one product were not always successful evaluating others. Few subjects were successful in everything. The conclusion was that there is only minor systematic decline with increasing complexity of products. The authors emphasize that definition of complexity involves more than just counting number of constituents and taste sensations, and suggest that minor differences in the task given to the assessor might explain different performances.

PRACTICAL APPLICATIONS

Practical use of the research presented in the present paper is in a sensory evaluation context. It is important for the users of sensory data to find out how the profiling should be organized to achieve optimum output, and in specific, the need for extensive training when dealing with a more complex product. The present study hypothesized that sensory assessors would have more difficulties evaluating a more complex product. However, the results showed that panel leaders should be more concerned with the task variables in the sensory evaluation. Even a minor shift in task variables had a stronger impact on the performance and reliability of the assessors than increasing number of constituents and/or stimuli sensations of the product. This study did not demonstrate a need for extensive training when dealing with a more complex product as hypothesized.