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Points out the steadily growing role of computers in the industrial sector. Highlights some accidents involving robots and touches on safeguards which have been introduced. Presents reliability and availability analysis of a robot machine/system having a redundant safety system. Formulas for system reliability, steady state availability, and mean time to failure are developed. Selective plots of the resulting formulas are shown.

This paper presents a review of published literature on robot reliability and safety. The literature is classified into three main categories: robot safety; robot reliability; and miscellaneous. Robot safety is further categorized into six classifications: general; accidents; human‐factors; safety standards; safety methods; and safety systems/technologies. The period covered by the review is from 1973 to 2001.

In recent years, the application of robots in different industrial sectors such as nuclear power generation, construction, automobile, firefighting and medicine, etc. is increasing day by day. In large industrial plants generally humans and robots work together to accomplish several tasks and lead to the problem of safety and reliability because any malfunction event of robots may cause human injury or even death. To access the reliability of a robot, sufficient amount of failure data is required which is sometimes very difficult to collect due to rare events of any robot failures. Also, different types of their failure pattern increase the difficulty which finally leads to the problem of uncertainty. To overcome these difficulties, this paper presents a case study by assessing fuzzy fault tree analysis (FFTA) to control robot-related accidents to provide safe working environment to human beings in any industrial plant.

Presented FFTA method uses different fuzzy membership functions to quantify different uncertainty factors and applies alpha-cut coupled weakest t-norm (Tω) based approximate fuzzy arithmetic operations to obtain fuzzy failure probability of robot-human interaction fault event which is the main contribution of the paper.

The result obtained from presented FFTA method is compared with other listing approaches. Critical basic events are also ranked using V-index for making suitable action plan to control robot-related accidents. Study indicates that the presented FFTA is a good alternative method to analyze fault in robot-human interaction for providing safe working environment in an industrial plant.

Existing fuzzy reliability assessment techniques designed for robots mainly use triangular fuzzy numbers (TFNs), triangle vague sets (TVS) or triangle intuitionistic fuzzy sets (IFS) to quantify data uncertainty. Present study overcomes this shortcoming and generalizes the idea of fuzzy reliability assessment for robots by adopting different IFS to control robot-related accidents to provide safe working environment to human. This is the main contribution of the paper.

This paper presents reliability and availability analyses of a robot‐safety system having one robot and n‐redundant safety units with common‐cause failures. The system failure rates and the partially failed system repair rates are assumed constant, and the failed system repair time is assumed arbitrarily distributed. Markov and the supplementary variable methods were used to perform mathematical analysis of this model. Generalized expressions for state probabilities, system availabilities, reliability, mean time to failure, and variance of time to failure are developed. Some plots of these expressions are shown.

The purpose of this paper is to study reliability, availability, and mean time to failure of a repairable robot‐safety system composed of n robots, m safety units, and a perfect switch.

Generalized expressions for system state probabilities, system availability, reliability, and mean time to failure are developed. Supplementary variable and Markov methods were used to develop these expressions.

This study clearly demonstrates that backup robots, safety units, and the repair process help to improve system availability.

This study will help maintenance engineers and reliability practitioners to become aware of the combined effect of backup robots, safety units, and the repair process on the performance of the robot‐safety system. Consequently, they will make better maintenance related decisions in organizations that make use of robots.

This paper has studied the effects of having redundant robots, safety units, and the repair facilities on the performance of a robot‐safety system with perfect mechanism to turn on a safety unit. This is one of the first attempts to study the combined effects of all these factors on a robot‐safety system.

This paper aims to conduct a comprehensive fault tree analysis (FTA) on the critical components of industrial robots. This analysis is integrated with the reliability block diagram (RBD) approach to investigate the robot system reliability.

For practical implementation, a particular autonomous guided vehicle (AGV) system was first modeled. Then, FTA was adopted to model the causes of failures, enabling the probability of success to be determined. In addition, RBD was used to simplify the complex system of the AGV for reliability evaluation purpose.

Hazard decision tree (HDT) was configured to compute the hazards of each component and the whole AGV robot system. Through this research, a promising technical approach was established, allowing decision-makers to identify the critical components of AGVs along with their crucial hazard phases at the design stage.

As complex systems have become global and essential in today’s society, their reliable design and determination of their availability have turned into very important tasks for managers and engineers. Industrial robots are examples of these complex systems that are being increasingly used for intelligent transportation, production and distribution of materials in warehouses and automated production lines.

The purpose of this paper is to study reliability, availability, and mean time to failure of a repairable robot‐safety system composed of (n−1) standby robots, a safety unit, and a switch.

Generalized expressions for system state probabilities, system availability, reliability, and mean time to failure are developed when the failure rates of robot and safety unit are constant and the failed system repair times are arbitrarily distributed. Supplementary variable and Markov methods were used to develop these expressions.

This study clearly demonstrates that standby robots and the repair process help to improve system availability.

This study will help maintenance engineers and reliability practitioners to become aware of the combined effect of standby robots and the repair process on the performance of the robot‐safety system. Consequently, they will make better maintenance related decisions in organizations such as automobile manufacturers that use robots quite frequently.

This paper has studied the effects of having redundant robots and the repair facilities on the performance of a robot‐safety system with perfect mechanism to turn on a standby robot. This is one of the first attempts to study the combined effects of all these factors on a robot‐safety system.

This paper aims to investigate using scanner-based adaptive neuro-fuzzy inference system (ANFIS), artificial neural networks (ANNs) and polynomial regression methods for prediction of silver nanoparticles (AgNPs) and dye concentrations on AgNP-treated silk fabrics.

For estimation of the dye and AgNPs concentration using image processing, the silk fabrics were scanned under the condition of 200 pixels per inch. The red green blue (RGB) values of scanned images were obtained after applying the median filter. Then, the relationship between scanner RGB values and dye and AgNPs concentrations were obtained by using artificial intelligence methods such as ANFIS and ANNs.

The best result was achieved by the ANFIS system for calculation concentration of dye with 0.07% error and concentration of AgNPs with 0.008 (gr/l) error. The obtained results indicate that the performance of the ANFIS system method is better than the other methods.

Using a scanner-based artificial intelligence technique for prediction of nanosilver and dye content on silk fabric.

The purpose of this paper is to demonstrate the effectiveness and advantages of using perceptual tolerance neighbourhoods in tolerance space‐based image similarity measures and its application in content‐based image classification and retrieval.

The proposed method in this paper is based on a set‐theoretic approach, where an image is viewed as a set of local visual elements. The method also includes a tolerance relation that detects the similarity between pairs of elements, if the difference between corresponding feature vectors is less than a threshold 2 (0,1).

It is shown that tolerance space‐based methods can be successfully used in a complete content‐based image retrieval (CBIR) system. Also, it is shown that perceptual tolerance neighbourhoods can replace tolerance classes in CBIR, resulting in more accuracy and less computations.

The main contribution of this paper is the introduction of perceptual tolerance neighbourhoods instead of tolerance classes in a new form of the Henry‐Peters tolerance‐based nearness measure (tNM) and a new neighbourhood‐based tolerance‐covering nearness measure (tcNM). Moreover, this paper presents a side – by – side comparison of the tolerance space based methods with other published methods on a test dataset of images.