Reducing the risk of failure by deliberate weaknesses

The deliberate weaknesses are points of weakness towards which a potential failure is channelled in order to limit the magnitude of the consequences from failure. The paper shows that reducing risk by deliberate weaknesses is a powerful domain-independent method which transcends mechanical engineering and works in various unrelated areas of human activity. A classification has been proposed of categories and classes of deliberate weaknesses reducing risk as well as discussion related to the underlying mechanisms of risk reduction. It is shown that introducing and repositioning existing weaknesses is an effective risk-reduction strategy which transcends engineering and can be applied in many unrelated domains. The paper shows that in the case where the cost of failure of the separate components in a system varies significantly, an approach based on deliberate weaknesses has a significant advantage to the equal-reliability/equal-strength design approach

Domain-independent approach to risk reduction

The popular domain-specific approach to risk reduction created the illusion that efficient risk reduction can be delivered successfully solely by using methods offered by the specific domain. As a result, many industries have been deprived from efficient risk reducing strategy and solutions. This paper argues that risk reduction is underlined by domain-independent methods and principles which, combined with knowledge from the specific domain, help to generate effective risk reduction solutions. In this respect, the paper introduces a powerful method for reducing the likelihood of computational errors based on combining the domain-independent method of segmentation and local knowledge of the chain rule for differentiation. The paper also demonstrates that lack of knowledge of domain-independent principles for risk reduction misses opportunities to reduce the risk of failure even in such mature field like stress analysis. The domain-independent methods for risk reduction do not rely on reliability data or knowledge of physical mechanisms underlying possible failure modes and are particularly well suited for developing new designs, with unknown failure mechanisms and failure history. In many cases, the reliability improvement and risk reduction by using the domain-independent methods reduces risk at no extra cost or at a relatively small cost. The presented domain-independent methods work across totally unrelated domains and this is demonstrated by the supplied examples which range from various areas of engineering and technology, computer science, project management, health risk management, business and even mathematics. The domain-independent risk reduction methods presented in this paper promote building products and systems characterised by high-reliability and resilience

Improving reliability and reducing risk by using inequalities

The paper introduces a powerful domain-independent method for improving reliability and reducing risk based on algebraic inequalities, which transcends mechanical engineering and can be applied in many unrelated domains. The paper demonstrates the application of inequalities to reduce the risk of failure by producing tight uncertainty bounds for properties and risk-critical parameters. Numerous applications of the upper-bound-variance inequality have been demonstrated in bounding uncertainty from multiple sources, among which is the estimation of uncertainty in setting positioning distance and increasing the robustness of electronic devices. The rearrangement inequality has been used to maximise the reliability of components purchased from suppliers. With the help of the rearrangement inequality, a highly counter-intuitive result has been obtained. If no information about the component reliability characterising the individual suppliers is available, purchasing components from a single supplier or from the smallest possible number of suppliers maximises the probability of a high-reliability assembly. The Cauchy-Schwartz inequality has been applied for determining sharp bounds of mechanical properties and the Chebyshev's inequality for determining a lower bound for the reliability of an assembly. The inequality of the inversely correlated random events has been introduced and applied for ranking risky prospects involving units with unknown probabilities of survival

Methods for reliability improvement and risk reduction

This chapter summarizes general guidelines on risk management. The common approach to risk reduction is the domain‐specific approach which relies heavily on root cause analysis and detailed knowledge from the specific domain. The domain‐specific approach to risk reduction created an illusion: that efficient risk reduction can be delivered successfully solely by using methods offered by the specific domain without resorting to general methods for risk reduction. The direct consequence of this illusion is that many industries have been deprived from effective risk‐reducing strategy and reliability improvement solutions. A common approach to reliability improvement is to select a statistical‐based, data‐driven approach. To overcome the major deficiency of the data‐driven approach, the chapter discusses the physics‐of‐failure approach. It also argues that many of the principles for technical risk reduction with general validity are rooted in the reliability and risk theory and cannot possibly be deduced from the general inventive principles formulated in TRIZ

Can system reliability be predicted from average component reliabilities?

The paper reveals that a prediction of system reliability on demand based on average reliabilities on demand of components is a fundamentally flawed approach. A physical interpretation of algebraic inequalities demonstrated that assuming average component reliabilities on demand entails an overestimation of the system reliability on demand for systems with components logically arranged in series and series-parallel and underestimation of the reliability on demand for systems with components logically arranged in parallel. The key reason for these discrepancies is the variability of components from the same type. Techniques for countering variability by promoting asymmetric response through inversion have also been introduced. The paper demonstrates that variability during assembly operations can affect negatively the reliability of mechanical systems. Accordingly, techniques for reducing the variability of stresses during assembly operations have been discussed. Finally, the paper provides a discussion related to the reasons for the relatively slow adoption of domain-independent methods for improving reliability despite their numerous advantages

Reliability improvement and risk reduction through self-reinforcement

The method of self-reinforcement has been introduced as a domain-independent method for improving reliability and reducing risk. A key feature of self-reinforcement is that increasing the external/internal forces intensifies the system‘s response against these forces. As a result, the driving net force towards precipitating failure is reduced. In many cases, the self-reinforcement mechanisms achieve remarkable reliability increase at no extra cost. Two principal ways of self-reinforcement have been identified: reinforcement by capturing a proportional compensating factor and reinforcement by using feedback loops. Mechanisms of transforming forces and motion into self-reinforcing response have been introduced and demonstrated through appropriate examples. Mechanisms achieving selfreinforcement response by self-aligning, self-anchoring and modified geometry have also been introduced For the first time, the potential of positive feedback loops to achieve self-reinforcement and risk reduction was demonstrated. In this respect, it is shown that self-energizing, fast growth and fast transition provided by positive feedback loops can be used with success for achieving reliability improvement. Finally, a classification was proposed of methods and techniques for reliability improvement and risk reduction based on the method of self-reinforcement

Improving reliability and reducing risk by minimizing the rate of damage accumulation

The paper introduces the principle of minimized rate of damage accumulation as a domain-independent principle of reliability improvement and risk reduction. A classification is proposed of methods for reducing the rate of damage accumulation. The paper introduces the method of substitution for reducing the rate of damage accumulation. The original assembly/system is substituted with assembly/system performing the same function and based on different physical principles. Such a substitution often eliminates failure modes characterised by intensive damage accumulation. One of the methods discussed is an optimal replacement resulting in the smallest rate of damage accumulation and maximum system reliability. A method for achieving the smallest rate of damage accumulation for a system with components logically arranged in series has been proposed for the first time. A dynamic programming algorithm for determining the optimal variation of multiple damage-inducing factors to minimize the rate of damage accumulation, has also been proposed for the first time. The paper shows that the necessary and sufficient condition for using the additivity rule for calculating the threshold of accumulated damage precipitating failure is the factorisation of the rate of damage accumulation into a function of the amount of damage and a function of the damage-inducing factor

Reliability and risk controlled by the simultaneous presence of random events on a time interval

The paper treats the important problem related to risk controlled by the simultaneous presence of critical events, randomly appearing on a time interval and shows that the expected time fraction of simultaneously present events does not depend on the distribution of events durations. In addition, the paper shows that the probability of simultaneous presence of critical events is practically insensitive to the distribution of the events durations. These counter-intuitive results provide the powerful opportunity to evaluate the risk of overlapping of random events through the mean duration times of the events only, without requiring the distributions of the events durations or their variance. A closed-form expression for the expected fraction of unsatisfied demand for random demands following a homogeneous Poisson process in a time interval is introduced for the first time. In addition, a closed-form expression related to the expected time fraction of unsatisfied demand, for a fixed number of consumers initiating random demands with a specified probability, is also introduced for the first time. The concepts stochastic separation of random events based on the probability of overlapping and the average overlapped fraction are also introduced. Methods for providing stochastic separation and optimal stochastic separation achieving balance between risk and cost of risk reduction are presented

Reliability improvement and risk reduction by inequalities and segmentation

The paper introduces new domain-independent methods for improving reliability and reducing risk based on algebraic inequalities and chain-rule segmentation. Two major advantages of algebraic inequalities for reducing risk have been demonstrated: (i) ranking risky prospects in the absence of any knowledge related to the individual building parts and (ii) reducing the variability of a risk-critical critical output parameter. The paper demonstrates a highly counter-intuitive result derived by using inequalities: if no information about the component reliability characterising the individual suppliers is available, purchasing components from a single supplier or from the smallest possible number of suppliers maximises the probability of a high-reliability assembly. The paper also demonstrates the benefits from combining domain-independent methods and domain-specific knowledge for achieving risk reduction in several unrelated domains: decision-making, manufacturing, strength of components and kinematic analysis of complex mechanisms. In this respect, the paper introduces the chain rule segmentation method and applies it to reduce the risk of computational errors in kinematic analysis of complex mechanisms. The paper also demonstrates that combining the domain-independent method of segmentation and domain-specific knowledge in stress analysis leads to a significant reduction of the internal stresses and reduction of the risk of overstress failure

Mechanisms for improving reliability and reducing risk by stochastic and deterministic separation

The paper provides for the first time a comprehensive introduction into the mechanisms through which the method of separation achieves risk reduction and into the ways it can be implemented in engineering designs. The concept stochastic separation of critical random events on a time interval, which consists of guaranteeing with a specified probability a specified degree of distancing between the random events, is introduced. Efficient methods for providing stochastic separation by reducing the duration times of overlapping critical random events on a time interval are presented. The paper shows that the probability of overlapping of critical events, randomly appearing on a time interval, is practically insensitive to the distribution of their duration times and to the variance of the duration times as long as the mean of the duration times remains the same. A rigorous proof is presented that this statement is valid even for two random events on a time interval. The paper also provides insight into various mechanisms through which deterministic separation improves reliability and reduces risk. It is demonstrated that the separation on properties is an efficient technique for compensating the drawbacks associated with homogeneous properties. It is demonstrated that improving reliability by including redundancy, improving reliability by segmentation and some of the deliberate weak link techniques and stress limiters techniques for reducing risk are effectively special cases of a deterministic separation. Finally, the paper demonstrates that in a number of cases, the way to extract benefit from the method of separation is to build and analyse a mathematical model based on the method of separation. A comprehensive classification of the discussed methods for stochastic and deterministic separation is also presented