The CRRM provides a valuable resource of knowledgeable personnel that can provide: objective evaluations of reliability and survivability assessment techniques, objective recommendations of approaches to meet reliability and survivability needs, and can develop new approaches or techniques to meet newly evolving needs in the reliability & survivability assessment and improvement arena. Decisions must constantly be made by industry and governments, regarding the development and deployment of new technologies, and the management and/or disposal of the waste products from older technologies. Standardized methods and concentrated expertise are required to help make these decisions.
Reliability and risk assessments for any engineering systems and technologies are similar in their basic structure. Whether the systems are mechanical or electronic or chemical, systems can be described in terms or their overall goals and functional requirements, as well as the hardware, software and human interfaces required to implement the functions. When systems are viewed in this manner, many of the reliability and risk assessment tools and techniques which have been developed till now are relevant. Such tools and techniques will be employed to assess various engineering systems, explore the ways in which such systems can fail as a result of internal failures and/or external attacks and analyze the risk implications of such events.
DEVELOPMENT AND APPLICATIONS OF MATHEMATICAL MODELS FOR MULTI-STATE SYSTEMS RELIABILITY AND MAINTENANCE
(Joint Germany-Israeli project)
Israel Team – Principal Investigators: Dr. Ilia Frenkel, Dr. Anatoly Lisniansky, Sami Shamoon College of Engineering.
Research Team: Dr. Lev Khvatskin,
Germany Team – Principal Investigator: Prof. Waltraud Kahle, Institute for Mathematical Stochastics, Otto-von-Guericke-University, Germany
Research Team: Prof. Gerd Christoph, Institute for Mathematical Stochastics, Otto-von-Guericke-University, Germany
Reliability and Maintenance Theory is enough well established for traditional binary-state systems where the system and each of its components may have only two possible states: perfect functionality (UP) and complete failure (DOWN). However, many real-world systems are composed of multi-state components, which have different performance levels and several failure modes with various effects on the entire system performance (degradation). Such systems are called multi-state systems (MSS). The examples of MSS are power systems where the component performance is characterized by the generating capacity, computer systems where the component performance is characterized by the data processing speed, pipe-line networks for oil and gas transmission etc. Till now many research works were done where many reliability and maintenance models were developed for binary-state systems. In order to determine optimal maintenance policies for real-world multi-state systems these models should be extended. This extension requires high-level research work where age replacement, block replacement, periodic replacement, incomplete repair models should be extended for Multi-state System as well as perfect and imperfect preventive maintenance and its modifications. The objective is to find optimal maintenance policies for these cases that will be different from corresponding optimal policies for binary-state system. The proposed research should establish the theoretical base for developing modern high reliable systems. The techniques will actually be used in various real-world multi-state systems such as computing systems, power systems, energy or material transmission systems, communication systems, radars etc., where failures during actual operation are costly or dangerous. For most of these systems maintainability associated costs are the main part of total Life Cycle Cost and applying of optimal maintenance policies (that should be found as a result of proposed research) will save a significant amount of money.
OPTIMAL DESIGN OF HIGH RELIABLE AIR-CONDITIONING SYSTEMS USED IN HEAVY WEATHER CONDITIONS VIA MARKOV REWARD MODELS
Principal Investigators: Dr. Ilia Frenkel, Dr. Lev Khvatskin, Sami Shamoon College of Engineering.
Research Team: Dr. Anatoly Lisniansky, Sami Shamoon College of Engineering.
Highly reliable and high-quality air conditioning is demanded by the growing economy. Critical facilities , such as medical and communication centers, Web hosts, financial services, hotels and high-tech manufacturing require a “7×24” continuous air-conditioning supply. To provide non-stop air-condition to a load of such end-users with a very high reliability, an air-conditioning system must be extremely reliable. Current systems fall far behind in their capacity to meet this reliability standard.
A real air-conditioning system, used in one of the high-level hotels, situated in area with heavy weather condition, include N active air-conditioners plus backup conditioner(s) in standby, where K conditioners (K<N) could provide sufficient air condition. If one of the active conditioners fails, the rest of the actives speed up and pick up the deficit cold. Meanwhile, a standby generator is getting started to form the system of a K-out-of-N configuration again, and the failed conditioner is undergoing repair.
Based on this real industrial application, generalized repairable system Markov Reward model, K-out-of-N plus M cold standby units, is proposed in this research. Reliability measures such as availability, mean number of system failures, mean time between failures and others will be been studied under several combinations of assumptions/cases: identical and different cold standby, perfect and imperfect switching and so on.
How to design this kind of air-conditioning system to achieve its reliability measures’ requirements will be studied . Factors that affect system reliability measures characteristics are presented. A real example of the defined system is provided through the developed approach. Reliability and availability of this air-conditioning system are evaluated, which is much more reliable than the existing one.