Abstract: Two mathematical models are developed in this paper to study the effectiveness of system administration effortson the improvement of system availability, based on the assumption that there exists a transitio...Abstract: Two mathematical models are developed in this paper to study the effectiveness of system administration effortson the improvement of system availability, based on the assumption that there exists a transitional state for a computer sys-tem in operation before it is brought down by some hardware or software problems and with intensified system administra-tion efforts, it is possible to discover and fix the problems in time to bring the system back to normal state before it isdown. Markov chain is used to simulate the transition of system states. A conclusion is made that increasing system admin-istration efforts may be a cost-effective way to meet the requirements for moderate improvement on system availability, buthigher demand on this aspect still has to be met by advanced technologies.展开更多
Recently,firms have begun to handle the design,manufacturing,and maintenance of capital goods through a consolidated mechanism called the integrated product-service system.This new paradigm enables firms to deliver hi...Recently,firms have begun to handle the design,manufacturing,and maintenance of capital goods through a consolidated mechanism called the integrated product-service system.This new paradigm enables firms to deliver high-reliability products while lowering the ownership cost.Hence,holistic optimization models must be proposed for jointly allocating reliability,maintenance,and spare parts inventory across the entire value chain.In the existing literature,these decisions are often made fragmentally,thus resulting in local optimality.This study reviews the extant works pertaining to reliability-redundancy allocation,preventative maintenance,and spare parts logistics models.We discuss the challenges and opportunities of consolidating these decisions under an integrated reliability-maintenance-inventory framework for attaining superior system availability.Specific interest is focused on the new product introduction phase in which firms face a variety of uncertainties,including installed base,usage,reliability,and trade policy.The goal is to call for tackling the integrated reliability-maintenance-inventory allocation model under a nonstationary operating condition.Finally,we place the integrated allocation model in the semiconductor equipment industry and show how the firm deploys reliability initiatives and after-sale support logistics to ensure the fleet uptime for its global customers.展开更多
Failures are normal rather than exceptional in the cloud computing environments. To improve system avai- lability, replicating the popular data to multiple suitable locations is an advisable choice, as users can acces...Failures are normal rather than exceptional in the cloud computing environments. To improve system avai- lability, replicating the popular data to multiple suitable locations is an advisable choice, as users can access the data from a nearby site. This is, however, not the case for replicas which must have a fixed number of copies on several locations. How to decide a reasonable number and right locations for replicas has become a challenge in the cloud computing. In this paper, a dynamic data replication strategy is put forward with a brief survey of replication strategy suitable for distributed computing environments. It includes: 1) analyzing and modeling the relationship between system availability and the number of replicas; 2) evaluating and identifying the popular data and triggering a replication operation when the popularity data passes a dynamic threshold; 3) calculating a suitable number of copies to meet a reasonable system byte effective rate requirement and placing replicas among data nodes in a balanced way; 4) designing the dynamic data replication algorithm in a cloud. Experimental results demonstrate the efficiency and effectiveness of the improved system brought by the proposed strategy in a cloud.展开更多
This research introduces a holistic framework called Design for Availablhty that uses me principles of Lean Sigma and Design for X to cost-effectively optimize the availability of capital goods (i.e., technical syste...This research introduces a holistic framework called Design for Availablhty that uses me principles of Lean Sigma and Design for X to cost-effectively optimize the availability of capital goods (i.e., technical systems used in the production of end-products or -services such as medical systems, airplanes, and manufacturing equipment) throughout their entire lifetime. Manufacturers require such a framework because users of capital goods increasingly insist on high system availability levels against reduced lifetime costs. The Design for Availability framework allows manufacturers to determine the current status of system availability and associated lifetime costs, and to identify opportunities to create additional value for themselves and their customers. A case study at a global manufacturer of capital goods in the food processing industry illustrates how the framework can be used in practice and to what extent the manufacturer and customers may profit from applying Design for Availability.展开更多
基金This project was supported by the National Key program of Science and Technology(99-A29-0101).
文摘Abstract: Two mathematical models are developed in this paper to study the effectiveness of system administration effortson the improvement of system availability, based on the assumption that there exists a transitional state for a computer sys-tem in operation before it is brought down by some hardware or software problems and with intensified system administra-tion efforts, it is possible to discover and fix the problems in time to bring the system back to normal state before it isdown. Markov chain is used to simulate the transition of system states. A conclusion is made that increasing system admin-istration efforts may be a cost-effective way to meet the requirements for moderate improvement on system availability, buthigher demand on this aspect still has to be met by advanced technologies.
文摘Recently,firms have begun to handle the design,manufacturing,and maintenance of capital goods through a consolidated mechanism called the integrated product-service system.This new paradigm enables firms to deliver high-reliability products while lowering the ownership cost.Hence,holistic optimization models must be proposed for jointly allocating reliability,maintenance,and spare parts inventory across the entire value chain.In the existing literature,these decisions are often made fragmentally,thus resulting in local optimality.This study reviews the extant works pertaining to reliability-redundancy allocation,preventative maintenance,and spare parts logistics models.We discuss the challenges and opportunities of consolidating these decisions under an integrated reliability-maintenance-inventory framework for attaining superior system availability.Specific interest is focused on the new product introduction phase in which firms face a variety of uncertainties,including installed base,usage,reliability,and trade policy.The goal is to call for tackling the integrated reliability-maintenance-inventory allocation model under a nonstationary operating condition.Finally,we place the integrated allocation model in the semiconductor equipment industry and show how the firm deploys reliability initiatives and after-sale support logistics to ensure the fleet uptime for its global customers.
基金Supported by the National Natural Science Foundation of China under Grant Nos. 61070162, 71071028 and 70931001the Specialized Research Fund for the Doctoral Program of Higher Education of China under Grant Nos. 20110042110024 and 20100042110025the Fundamental Research Funds for the Central Universities of China under Grant Nos. N100604012, N090504003 and N090504006
文摘Failures are normal rather than exceptional in the cloud computing environments. To improve system avai- lability, replicating the popular data to multiple suitable locations is an advisable choice, as users can access the data from a nearby site. This is, however, not the case for replicas which must have a fixed number of copies on several locations. How to decide a reasonable number and right locations for replicas has become a challenge in the cloud computing. In this paper, a dynamic data replication strategy is put forward with a brief survey of replication strategy suitable for distributed computing environments. It includes: 1) analyzing and modeling the relationship between system availability and the number of replicas; 2) evaluating and identifying the popular data and triggering a replication operation when the popularity data passes a dynamic threshold; 3) calculating a suitable number of copies to meet a reasonable system byte effective rate requirement and placing replicas among data nodes in a balanced way; 4) designing the dynamic data replication algorithm in a cloud. Experimental results demonstrate the efficiency and effectiveness of the improved system brought by the proposed strategy in a cloud.
文摘This research introduces a holistic framework called Design for Availablhty that uses me principles of Lean Sigma and Design for X to cost-effectively optimize the availability of capital goods (i.e., technical systems used in the production of end-products or -services such as medical systems, airplanes, and manufacturing equipment) throughout their entire lifetime. Manufacturers require such a framework because users of capital goods increasingly insist on high system availability levels against reduced lifetime costs. The Design for Availability framework allows manufacturers to determine the current status of system availability and associated lifetime costs, and to identify opportunities to create additional value for themselves and their customers. A case study at a global manufacturer of capital goods in the food processing industry illustrates how the framework can be used in practice and to what extent the manufacturer and customers may profit from applying Design for Availability.