Performance Analysis of an FMS Operating Under Different Failure Rates and Maintenance Policies

Flexible manufacturing Systems (FMSs) typically operate at 70–80% utilization, which is much higher than the utilization of traditional machines that can operate with as low as 20% utilization. A result is that an FMS may incur four times more wear and tear than a traditional system. This requests the execution of effective maintenance plans on FMSs. While maintenance actions can reduce the effects of breakdowns due to wear-outs, random failures are still unavoidable. It is important to understand the implications of a given maintenance plan on an FMS before its implementation. This paper discusses a procedure that combines simulation and analytical models to analyze the effects of corrective, preventive, and opportunistic maintenance policies on the performance of an FMS. The FMS performance is measured by its operational availability index, which is determined using the production output rate of the FMS under a variety of time between failure distributions and different operational conditions. The effects of various maintenance policies on FMS performance are simulated and the results are compared to determine the best policy for a given system.     

Maintenance Integration in Manufacturing Systems: From the Modeling Tool to Evaluation

In manufacturing systems, wear-out and eventual failure are unavoidable. However, to reduce the rate of their occurrence and to prolong the life of equipment or the capacity for extended productive use of the equipment under the necessary technological functioning and servicing, maintenance can be performed. For large manufacturing systems, maintenance integration involves a particular development concerned with both complexity models and computing time. This paper presents an effective way of modeling complex manufacturing systems through hierarchical and modular analysis by using stochastic Petri nets and Markov chains. In the proposed approach, the integration of maintenance policies in a manufacturing system is facilitated by the development of a generic model. With this generic modeling, the user doesn't need to code the strategies but only to instantiate the generic model with the structure of the manufacturing system. This method allows various maintenance strategies to be coded in the generic model with the aim of studying their influence on system dependability and performance.     

Assessing the structural complexity of manufacturing systems configurations

Modern manufacturing systems are increasingly required to be flexible and adaptable to changing market demands, which adds to their structural and operational complexity. One of the major challenges at the early design stages is to select a manufacturing system configuration that both satisfies the production functional requirements and is easy to operate and manage. A new metric for assessing the structural complexity of manufacturing system configurations is presented in this paper. The proposed complexity metric incorporates the quantity of information using an entropy approach. It accounts for the complexity inherent in the various modules in the manufacturing system through the use of an index derived from a newly developed manufacturing systems classification code. The code captures the effect of various component types and technologies used in a manufacturing system on the system’s structural complexity. The presented metric would be helpful in selecting the least complex manufacturing system configuration that meets the requirements. An engine cylinder head production system is used to illustrate the application of the proposed methodology in comparing feasible but different manufacturing system configurations capable of producing the cylinder head based on their structurally inherent complexity.     

A model management systems approach to manufacturing systems design

Manufacturing systems design involves the solution of a complex series of interrelated problems. This complexity will increase in the future as manufacturing practices change to meet increased global competition. Research within manufacturing systems design has mainly been focused on finding improved models for solving particular problems, or extending existing modeling techniques. This has resulted in numerous modeling tools being available to support manufacturing systems design. However, little research work has been carried out into consolidating the existing theories and models. As a result, a large body of this work has not been applied in industry. Model management has evolved as a research area which investigates methods for storing, modifying, and manipulating models. This article describes a prototype model management system for manufacturing systems design. The objective here is not to develop “another” decision support system for manufacturing design, but to illustrate, through the development of a prototype system, a number of key ideas of how concepts from the area of model management systems can be used to support manufacturing systems design. The prototype model management system utilizes the structured modeling framework and uses an extended version of the structured modeling language. An important aspect of the prototype model management system is the incorporation of the model development task, thus allowing the system to be easily updated and adapted. The prototype system was evaluated using a range of queueing network models for manufacturing systems design.     

Improved responsiveness of reconfigurable manufacturing systems using a standards-based approach to assess manufacturing capacity

Market acceptance of the S95 enterprise-control system integration standard and its adoption in IEC 62264, combined with the use of the ISO 15745 application integration scheme, offers a common framework for integrating diagnostic and control activities with asset maintenance and management activities. This paper describes a standard-based approach to improve the responsiveness of reconfigurable systems by using condition-based maintenance and diagnostics information to assess manufacturing capacity. Use of integration models and interoperability schemas enable manufacturing management to have greater visibility into the current state and the capabilities of manufacturing assets to meet scheduled manufacturing requirements.     

Reliability Measurement for Mixed Mode Failures of 33/11 Kilovolt Electric Power Distribution Stations

The reliability of the electrical distribution system is a contemporary research field due to diverse applications of electricity in everyday life and diverse industries. However a few research papers exist in literature. This paper proposes a methodology for assessing the reliability of 33/11 Kilovolt high-power stations based on average time between failures. The objective of this paper is to find the optimal fit for the failure data via time between failures. We determine the parameter estimation for all components of the station. We also estimate the reliability value of each component and the reliability value of the system as a whole. The best fitting distribution for the time between failures is a three parameter Dagum distribution with a scale parameter and shape parameters and . Our analysis reveals that the reliability value decreased by 38.2% in each 30 days. We believe that the current paper is the first to address this issue and its analysis. Thus, the results obtained in this research reflect its originality. We also suggest the practicality of using these results for power systems for both the maintenance of power systems models and preventive maintenance models.     

Economic and strategic perspectives on investing in RMS and FMS

The evolution of manufacturing systems, according to changing internal and external conditions, requires design and assessment techniques that consider both strategic and financial criteria to evaluate the suitability of the Flexible and Reconfigurable system solutions in addressing these variations. In this paper, a fuzzy multi-objective mixed integer optimization model to evaluate RMS investments used in a multiple product demand environment is presented. The model incorporates in-house production and outsourcing options, machine acquisition and disposal costs, operational costs, and re-configuration cost and duration for the utilized modular machines. The resulting system configurations are optimized for lifecycle costs, responsiveness performance, and system structural complexity simultaneously. A complexity metric that incorporates the quantity of information using an entropy approach is used to represent the inherent structural complexity of the considered system configurations. It accounts for the complexity of the machine modules in a manufacturing system through the use of an index derived from a newly developed manufacturing systems classification code, which captures the effect machine types and technologies on the system’s structural complexity. A metric is proposed to measure the responsiveness ability and efficiency as well as the overall capability of each machine and effectiveness of machines changeover. The application of the developed planning and assessment model that incorporates these three criteria is illustrated with a case study where FMS and RMS alternatives were compared. The suitable conditions for investing in RMS are also discussed.     

Approaches to Quality Risk Management When Using Single-Use Systems in the Manufacture of Biologics

Biologics manufacturing technology has made great progress in the last decade. One of the most promising new technologies is the single-use system, which has improved the efficiency of biologics manufacturing processes. To ensure safety of biologics when employing such single-use systems in the manufacturing process, various issues need to be considered including possible extractables/leachables and particles arising from the components used in single-use systems. Japanese pharmaceutical manufacturers, together with single-use suppliers, members of the academia and regulatory authorities have discussed the risks of using single-use systems and established control strategies for the quality assurance of biologics. In this study, we describe approaches for quality risk management when employing single-use systems in the manufacturing of biologics. We consider the potential impact of impurities related to single-use components on drug safety and the potential impact of the single-use system on other critical quality attributes as well as the stable supply of biologics. We also suggest a risk-mitigating strategy combining multiple control methods which includes the selection of appropriate single-use components, their inspections upon receipt and before releasing for use and qualification of single-use systems. Communication between suppliers of single-use systems and the users, as well as change controls in the facilities both of suppliers and users, are also important in risk-mitigating strategies. Implementing these control strategies can mitigate the risks attributed to the use of single-use systems. This study will be useful in promoting the development of biologics as well as in ensuring their safety, quality and stable supply.KEY WORDS: biologics, manufacturing technology, quality risk management, regulatory science, single-use system     

Life cycle assessment of water-based acrylic floor finish maintenance programs

Aim, Scope, and Background Industrial and institutional (I and I) floor maintenance activities require regular use of chemical products and equipment. Different floor care systems require different maintenance products, activities, and frequencies which consume different levels of energy and material for product manufacturing, maintenance, and application. Therefore, selecting between floor maintenance products and programs requires comprehensive analysis of the entire floor maintenance system as well as any site-specific factors that can influence human and environmental health. In this paper, a probabilistic model for comparing the environmental life cycle implications of I and I floor maintenance programs is presented. The primary interest is in comparing programs that use different water-based acrylic floor finishes and in particular, programs using zinc-containing floor finishes compared to zinc-free floor finish systems. Zinc, used in some acrylic polymers as a polymer cross-linking agent, is regulated in some communities to minimize its impact on the aquatic environment. Method The life cycle assessment (LCA) model was developed in compliance with the ISO 14040 series of standards [1]. Furthermore, uncertain input variables were defined as probabilistic distributions and Latin Hypercube Sampling was used to propagate uncertainty through the model. The scope of the study includes the full life cycle of the materials, supplies, equipment, and activities associated with performing floor maintenance. The effects of maintaining higher lighting and temperature levels while performing floor maintenance are estimated using building energy system analysis. The life cycle inventory (LCI) element of the LCA was developed using product-specific data, publicly available data, and established life cycle inventory databases. Life cycle impact assessment was conducted using the Eco-Indicator 99 [2] and Impact 2002+ [3,4] impact assessment methods. Results Two floor maintenance scenarios were developed and analyzed to compare the environmental impact of programs using zinc-containing and zinc-free floor finishes. The results discussed herein are presented for a hypothetical retail store located in the Midwest region of the United States. Given the scenarios examined, zinc-free floor finish systems reduced the release of zinc ions to the environment, but the overall impact in all life cycle impact assessment (LCIA) categories was greater for the zincfree floor finish system primarily due to the increased frequency of maintenance. Discussion The impacts associated with operating the facility were orders of magnitude higher than those associated with producing or using floor care products, supplies, or equipment. This leads to the conclusion that for critical impacts, floor care product development should focus research efforts on innovative products that reduce application and maintenance time if significant reduction in these impacts is sought. Conclusions Adopting a stochastic modeling approach enabled incorporation of parameter uncertainty and analysis of uncertainty in model results. In the scenario shown here, the magnitude of overall impact in all LCIA categories was greater for the zinc-free floor finish system than the zinc-containing floor finish system. Perspectives Use of decision modeling software provided flexibility for developing scenarios and assessing floor maintenance programs under various operational and site-specific conditions.     

Incorporating the impacts of climate change into infrastructure life cycle assessments: A case study of pavement service life performance

Climate change is expected to impact both the operational and structural performance of infrastructures such as roads, bridges, and buildings. However, most past life cycle assessment (LCA) studies do not consider how the operational/structural performance of infrastructure will be affected by a changing climate. The goal of this research was to develop a framework for integrating climate change impacts into LCA of infrastructure systems. To illustrate this framework, a flexible pavement case study was considered where life‐cycle environmental impacts were compared across a climate change scenario and several time horizons. The Mechanistic‐Empirical Pavement Design Guide (MEPDG) was utilized to capture the structural performance of each pavement performance scenario and performance distresses were used as inputs into a pavement LCA model that considered construction and maintenance/rehabilitation materials and activities, change in relative surface albedo, and impacts due to traffic. The results from the case study suggest that climate change will likely call for adaptive design requirements in the latter half of this century but in the near‐to‐mid term, the international roughness index (IRI) and total rutting degradation profile was very close to the historical climate run. While the inclusion of mechanistic performance models with climate change data as input introduces new uncertainties to infrastructure‐based LCA, sensitivity analyses runs were performed to better understand a comprehensive range of result outcomes. Through further infrastructure cases the framework could be streamlined to better suit specific infrastructures where only the infrastructure components with the greatest sensitivity to climate change are explicitly modeled using mechanistic‐empirical modeling routines.     

Operational seasonal forecasting of crop performance

Integrated, interdisciplinary crop performance forecasting systems, linked with appropriate decision and discussion support tools, could substantially improve operational decision making in agricultural management. Recent developments in connecting numerical weather prediction models and general circulation models with quantitative crop growth models offer the potential for development of integrated systems that incorporate components of long-term climate change. However, operational seasonal forecasting systems have little or no value unless they are able to change key management decisions. Changed decision making through incorporation of seasonal forecasting ultimately has to demonstrate improved long-term performance of the cropping enterprise. Simulation analyses conducted on specific production scenarios are especially useful in improving decisions, particularly if this is done in conjunction with development of decision-support systems and associated facilitated discussion groups. Improved management of the overall crop production system requires an interdisciplinary approach, where climate scientists, agricultural scientists and extension specialists are intimately linked with crop production managers in the development of targeted seasonal forecast systems. The same principle applies in developing improved operational management systems for commodity trading organizations, milling companies and agricultural marketing organizations. Application of seasonal forecast systems across the whole value chain in agricultural production offers considerable benefits in improving overall operational management of agricultural production.     

An overview of energy efficiency techniques in cluster computing systems

Two major constraints demand more consideration for energy efficiency in cluster computing: (a) operational costs, and (b) system reliability. Increasing energy efficiency in cluster systems will reduce energy consumption, excess heat, lower operational costs, and improve system reliability. Based on the energy-power relationship, and the fact that energy consumption can be reduced with strategic power management, we focus in this survey on the characteristic of two main power management technologies: (a) static power management (SPM) systems that utilize low-power components to save the energy, and (b) dynamic power management (DPM) systems that utilize software and power-scalable components to optimize the energy consumption. We present the current state of the art in both of the SPM and DPM techniques, citing representative examples. The survey is concluded with a brief discussion and some assumptions about the possible future directions that could be explored to improve the energy efficiency in cluster computing.     

Enhancement of microbiome management by machine learning for biological wastewater treatment

Here, we propose to develop microbiome-based machine learning models to predict the response of biological wastewater treatment systems to environmental or operational disturbances or to design specific microbiomes to achieve a desired system function. These machine learning models can be used to enhance the stability of microbiome-based biological systems and warn against the failure of these systems.     

A Systems Model Approach to Determining Resilience Surrogates for Case Studies

Resilience theory offers a framework for understanding the dynamics of complex systems. However, operationalizing resilience theory to develop and test empirical hypotheses can be difficult. We present a method in which simple systems models are used as a framework to identify resilience surrogates for case studies. The process of constructing a systems model for a particular case offers a path for identifying important variables related to system resilience, including the slowly-changing variables and thresholds that often are keys to understanding the resilience of a system. We develop a four-step process for identifying resilience surrogates through development of systems models. Because systems model development is often a difficult step, we summarize four basic existing systems models and give examples of how each may be used to identify resilience surrogates. The construction and analysis of simple systems models provides a useful basis for guiding and directing the selection of surrogate variables that will offer appropriate empirical measures of resilience.     

PACS的高级预防维护技术

目的 通过讨论PACS高级预防维护技术,供同他人在日常维护过程中有一定地借鉴作用.方法 从PACS数据库性能检测与优化,存储设备检测及PACS各应用软件模块三方面进行阐述.结果 经过医院一线安装维护人员和PACS厂家多年实践的总结,拥有一定的可参考依据.结论 PACS的高级预防维护是一个复杂的系统工程,包括一般维护和高级维护在内的实践理论才刚刚起步,科学的、规范化的预防维护需要不断地完善和发展.     

Clogging in subsurface-flow treatment wetlands: Occurrence and contributing factors

Clogging is a major operational and maintenance issue associated with the use of subsurface flow wetlands for wastewater treatment, and can ultimately limit the lifetime of the system. This review considers over two decades of accumulated knowledge regarding clogging in both vertical and horizontal subsurface flow treatment wetlands. The various physical, chemical and biological factors responsible for clogging are identified and discussed. The occurrence of clogging is placed into the context of various design and operational parameters such as wastewater characteristics, upstream treatment processes, intermittent or continuous operation, influent distribution, and media type. This information is then used to describe how clogging develops within, and subsequently impacts, common variants of subsurface flow treatment wetland typically used in the U.S., U.K., France and Germany. Comparison of these systems emphasized that both hydraulic loading rate and solids loading rate need to be considered when designing systems to operate robustly, i.e. hydraulic overloading makes horizontal-flow tertiary treatment systems in the U.K. more susceptible to clogging problems than vertical-flow primary treatment systems in France. Future research should focus on elucidating the underlying mechanisms of clogging as they relate to the design, operation, and maintenance of subsurface flow treatment wetlands.     

Information-Based Dynamic Manufacturing System Scheduling

Information about the state of the system is of paramount importance in determining the dynamics underlying manufacturing systems. In this paper, we present an adaptive scheduling policy for dynamic manufacturing system scheduling using information obtained from snapshots of the system at various points in time. Specifically, the framework presented allows for information-based dynamic scheduling where information collected about the system is used to (1) adjust appropriate parameters in the system and (2) search or optimize using genetic algorithms. The main feature of this policy is that it tailors the dispatching rule to be used at a given point in time to the prevailing state of the system. Experimental studies indicate the superiority of the suggested approach over the alternative approach involving the repeated application of a single dispatching rule for randomly generated test problems as well as a real system. In pa ticular, its relative performance improves further when there are frequent disruptions and when disruptions are caused by the introduction of tight due date jobs and machine breakdown—two of the most common sources of disruption in most manufacturing systems. From an operational perspective, the most important characteristics of the pattern-directed scheduling approach are its ability to incorporate the idiosyncratic characteristics of the given system into the dispatching rule selection process and its ability to refine itself incrementally on a continual basis by taking new system parameters into account.     

Integrated Modeling Framework for Manufacturing Systems: A Unified Representation of the Physical Process and Information System

The task of process modeling in a manufacturing environment centers around controlling and improving the flow of materials. This flow comprises a complicated web of control and physical systems. Despite a variety of manufacturing system modeling approaches, more rigorous process modeling is required. This paper presents an integrated modeling framework for manufacturing systems (IMF-M). Conceptual modeling of physical materials flow supported by a graphical representation facilitates improvement of operations in manufacturing environments. A declarative and executable representation of control information systems helps to improve information management by managing a variety of information models with improved readability and reusability. A unified representation of the physical process and information system provides a common modeling milieu in which efforts can be coordinated among several groups working in the different domains of scheduling, shop floor and logistics control, and information system. Since the framework helps adapt to the changes of the physical process and information system affecting each other in a consistent manner, the modeling output enhances integration of the manufacturing system.