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Presents two newly developed Markov models (I and II) to perform reliability analysis of a system composed of a robot and its associated safety system. Model I presents expressions for robot reliability, mean time between failure, and state probabilities under non‐repairable conditions. Similarly, Model II presents reliability, mean time to failure, and state probability expressions for a repairable robot system. Shows plots for robot system reliability and mean time to failure.

The purpose of this paper is to estimate the required number of robots consisting of some non-repairable components, by employing a renewal model. Considering the importance of the availability of standby autonomous robots for reducing and preventing down-times of advanced production systems, which imposes a considerable loss, the present research tries to introduce a practical model for the determination of the required number of autonomous robots.

Most of the available research on the estimation of the required standby components based on the reliability characteristics of components has not considered the environmental factors influencing the reliability characteristics. Therefore, such estimations are not accurate enough. In contrast, this paper focuses on the influence of the environmental and human factors (e.g. the operators’ skill) on the robot reliability characteristics.

A model based on the Weibull renewal process combined with the cold standby strategy is developed for reliability evaluation of the system. The effectiveness of the proposed integrated reliability evaluation model is worked out in some cases.

Determining a required number of robots is an important issue in availability and utilization of a complex robotic production system. In an advanced production system, while the estimation process of a required number of robots can be performed through different approaches, one of the realistic estimation methods is based on the system’s reliability that takes into consideration the system operating environment. To forecast the required number of robots for an existing production system, in some cases, the assumption of a constant failure rate does not differ much from the assumption of a non-constant failure rate and can be made with an acceptable error.

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.

This paper presents the results of a survey of Canadian robot users concerning robot reliability and safety. Data on 26 questions were analyzed and the resulting findings are presented in the form of tables, histograms, pie charts, etc. Provides conclusions including the fact that approximately 75 per cent of companies are using robots for commercial purposes; most general types of robots used in industry are intelligent robots; frequently ineffective maintenance manuals are provided by the robot manufacturers; and robot‐related problems are generally less than 50 per year.

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.

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 study aims to obtained the failure probability distributions of subsystems for industrial robot and filtrate its fault data considering the complicated influencing factors of failure rate for industrial robot and numerous epistemic uncertainties.

A fault data screening method and failure rate prediction framework are proposed to investigate industrial robot. First, the failure rate model of the industrial robot with different subsystems is established and then the surrogate model is used to fit bathtub curve of the original industrial robot to obtain the early fault time point. Furthermore, the distribution parameters of the original industrial robot are solved by maximum-likelihood function. Second, the influencing factors of the new industrial robot are quantified, and the epistemic uncertainties are refined using interval analytic hierarchy process method to obtain the correction coefficient of the failure rate.

The failure rate and mean time between failure (MTBF) of predicted new industrial robot are obtained, and the MTBF of predicted new industrial robot is improved compared with that of the original industrial robot.

Failure data of industrial robots is the basis of this prediction method, but it cannot be used for new or similar products, which is the limitation of this method. At the same time, based on the series characteristics of the industrial robot, it is not suitable for parallel or series-parallel systems.

This investigation has important guiding significance to maintenance strategy and spare parts quantity of industrial robot. In addition, this study is of great help to engineers and of great significance to increase the service life and reliability of industrial robots.

This investigation can improve MTBF and extend the service life of industrial robots; furthermore, this method can be applied to predict other mechanical products.

This method can complete the process of fitting, screening and refitting the fault data of the industrial robot, which provides a theoretic basis for reliability growth of the predicted new industrial robot. This investigation has significance to maintenance strategy and spare parts quantity of the industrial robot. Moreover, this method can also be applied to the prediction of other mechanical products.

To demonstrate the theory and effectiveness of reliability‐improvement countermeasures for line equipment, specifically industrial robots for automotive production engineering.

Suggests an efficient method of life‐cycle maintenance. The defects of industrial robots are analysed using Weibull analysis.

From the analysis, a strategy of countermeasures is framed for component screening, reliability design and lifetime estimation.

This method has been implemented worldwide in Toyota's factories, and has produced a better operating life cycle for industrial robots.

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.