Performance Theatre and the Poetics of Failure: Forced Entertainment, Goat Island, Elevator Repair Service (review)

2011 ◽  
Vol 63 (4) ◽  
pp. 675-676
Author(s):  
Ira S. Murfin
Keyword(s):  
Repair Service ◽  
Forced Entertainment

Causes of gear pump fails and methods for their elimination

2020 ◽  
pp. 98-107
Author(s):  
Vitaliy A. Zuyevskiy ◽  
Daniil O. Klimyuk ◽  
Ivan A. Shemberev
Keyword(s):  
Adhesion Strength ◽  
Production Systems ◽  
Low Cost ◽  
High Strength ◽  
Strength Properties ◽  
Research Purpose ◽  
Working Fluid ◽  
Gear Pump ◽  
Repair Service ◽  
Recovery Method

Gear pumps are an important element of many production systems and their replacement in case of failure can be quite expensive, so it is important to have a modern and well-tuned technology for their recovery. There are many methods for restoring the pump's performance, depending on the reason that led to its failure. (Research purpose) The research purpose is in determining what causes most often lead to loss of pump performance, and developing a recovery method that provides the greatest post-repair service life of the pump and low cost of repair. (Materials and methods) Authors took into account that the applied coatings must have sufficient adhesion strength and resistance to mechanical, thermal and corrosion loads during operation. It was found that most often significant leaks of the working fluid, leading to failure, occur due to an increase in the gap between the inner surface of the housing and the gears due to active wear of the housing wells. Authors determined that the method of electric spark treatment of worn-out housing wells is best suited to perform the task (a large post-repair resource and low costs). (Results and discussion) It was found by laboratory studies of the adhesion strength of electric spark coatings with various electrodes that the best transfer of the material to the substrate is provided by bronze electrodes BrMKts3-1. It was noted that the coatings applied using the BrMKts3-1 electrode have high strength properties. (Conclusions) Research conducted in the center for collective use "Nano-Center" VIM confirmed the possibility of effective recovery of the gear pump by electric spark treatment.

Consumer Responses to Service Failures: A Resource Preference Model of Cultural Influences

2008 ◽  
Vol 16 (1) ◽  
pp. 72-97 ◽  
Author(s):  
Haksin Chan ◽  
Lisa C. Wan
Keyword(s):  
Interactive Effect ◽  
Cultural Influences ◽  
Cross Cultural ◽  
Repair Service ◽  
Theoretical Understanding ◽  
Preference Model ◽  
Consumer Responses ◽  
Service Failures ◽  
Process Failure ◽  
Resource Preference

This article highlights consumers’ preference for economic (versus social) resources in individualist (versus collectivist) cultures and demonstrates the multifaceted effects of culture on consumer responses to service failures. A cross-cultural study involving American and Chinese participants in the setting of a computer repair service confirms seven of eight hypotheses derived from the resource preference model. The results indicate that Americans (versus Chinese) are more dissatisfied with an outcome failure but less dissatisfied with a process failure. This interactive effect of culture and failure type seems to be driven by a corresponding pattern of attribution tendencies across cultures. Not only do Americans and Chinese differ in service dissatisfaction, but they also tend to express their dissatisfaction in different ways, preferring voice and private responses, respectively. Overall, the resource preference model enhances theoretical understanding of cross-cultural consumer behavior and provides culture-specific guidelines for managing the inevitable service failures.

Forecasting Repair and Maintenance Services of Medical Devices Using Support Vector Machine

2021 ◽  
Author(s):  
Hao-yu Liao ◽  
Willie Cade ◽  
Sara Behdad
Keyword(s):  
Machine Learning ◽  
Support Vector Machine ◽  
Medical Devices ◽  
Kernel Functions ◽  
Support Vector ◽  
Quality Level ◽  
Learning Tools ◽  
Physical Damage ◽  
Repair Service ◽  
Product Failure

Abstract Accurate prediction of product failures and the need for repair services become critical for various reasons, including understanding the warranty performance of manufacturers, defining cost-efficient repair strategies, and compliance with safety standards. The purpose of this study is to use machine learning tools to analyze several parameters crucial for achieving a robust repair service system, including the number of repairs, the time of the next repair ticket or product failure, and the time to repair. A large dataset of over 530,000 repairs and maintenance of medical devices has been investigated by employing the Support Vector Machine (SVM) tool. SVM with four kernel functions is used to forecast the timing of the next failure or repair request in the system for two different products and two different failure types, namely random failure and physical damage. A frequency analysis is also conducted to explore the product quality level based on product failure and the time to repair it. Besides, the best probability distributions are fitted for the number of failures, the time between failures, and the time to repair. The results reveal the value of data analytics and machine learning tools in analyzing post-market product performance and the cost of repair and maintenance operations.

ASSESSMENT AND FORECASTING OF FREIGHT CAR TECHNICAL STATE

2021 ◽  
Vol 2021 (5) ◽  
pp. 40-47
Author(s):  
Elena Rozhkova
Keyword(s):  
Graphical Model ◽  
Technical State ◽  
Distribution Law ◽  
Repair Service ◽  
Statistic Modeling ◽  
Average Operating ◽  
Freight Car ◽  
Run Up ◽  
Definition Of ◽  
The Given

The purpose of this work is the assessment and forecasting of freight car technical state at life stages. The scientific novelty consists in the definition of car operating run-up to the first failure and between failures, and also in the definition of car life to considerable repair fulfillment from the operating run between failures and development of a graphical model of freight car reliability. As a result of the statistic modeling of gondola car operating runs up to the first failure it is defined that the given random value conforms to a normal distribution law, the first car setoff in TOR due to wear failure takes place at the operating run of 85,000 km. Besides the operating run-up to the first failure there was defined an operating run-up between failures. It is proved that the operating run-up between failures conforms to the exponential law of distribution, the mathematical expectation of which is 13,000 km. The results of investigations mentioned above formed the basis of the graphical model of car reliability. An inter-repair service life of a car can be represented as a sum of the following operating run-ups: operating run-ups to the first failure, the product of operating run-ups between failures and the number of failures and a residual operating run-up (from the utmost current repair to the nearest scheduled repair). On the basis of the mentioned it is expedient to consider a technology for the realization of an enlarged repair with the purpose of the repetition exclusion in car setoffs during the inter-repair term. On the basis of the simulator there is obtained the dependence of the frequency of car enlarged current repair fulfillment depending on average operating run-up between failures. At present an enlarged current repair must be carried out only for gondola cars in the planned order after having reached 80,000 km. The repair mentioned can be carried out both under depot conditions, and under conditions of repair workshops. The advantage of such a system of repair consists in the increase car work reliability during the inter-repair term.

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