Failure Mode Avoidance: How to Design and Avoid Failure - Report Example

FAILURE MODE AVOIDANCE: HOW TO DESIGN AND AVOID FAILURE + Submitted Automobile safety depends on design and practice, equipment, construction and regulation of automotives. Safe design reduces cases of accidents and preserves lives. It is the role of mechanical engineers to design systems that meet the standards of safety worldwide. It is necessary to comprehend the time and the circumstances under which potential failure modes are created in order to enable failure mode avoidance. A system that is deemed reliable needs to be robust. The system must avoid failure modes even in the presence of a large array of conditions that include changing operational demands, internal deteriorations and harsh environments. This task codifies and discusses the techniques for ensuring robust systems, which operate by increasing the range of conditions that the system can function under. It introduces a distinction between two-sided and one-sided failure modes (Birolini 2007, 83). It also proposes four strategies for creating larger windows between different sets of one-sided failure mode. It takes into account the fact that reliability is one of the most significant facets of mechanical engineering and automotive design. Reliability in Mechanical Engineering refers to the proper functioning of a mechanical system under a complete range of conditions experienced in the mechanical engineering field. Reliability requires two critical conditions to be realized; robustness and mistake avoidance. List of Abbreviations TRIZ: Theory of Inventive Problem Solving FMA: Failure Mode Avoidance OW: Operating Windows FMEA: Failure Mode and Effects Analysis Explanation of Terms In the case of Failure Mode Avoidance, the term ‘mistake’ refers to the plethora of manufacturing operations and design operations that may lead to gross error; and in this case, automotive devices. For instance, mistakes such as installation of a switch backwards and misinterpretation of software commands expressed in inches as though expressed in centimeters could lead to gross operational errors (McGill 2007, 40). Reliability of machinery and systems in the mechanical engineering field can be reduced by being weary of these common and silly mistakes. This takes a combination of problem-solving processes and knowledge-based engineering. ‘Robustness’ as pointed out as one of the essentials of failure mode avoidance refers to the ability of a system to function and avoid failure under the full array of conditions that are experienced in the field (McGill 2007, 40). It is a big challenge for mechanical engineers to develop a system that functions perfectly under the tightly controlled laboratory conditions. The challenge to have the same system that was developed in laboratory conditions to function well in real world conditions under different operational conditions is immense. Effective engineering that delivers a robust system is, therefore, a huge challenge for mechanical engineers (McGill 2007, 40). Fig 1: Showing some causes of System Failure (Braunwart 2007, 20) FMEA and the Common Causes of Automobile Failure Assessment of the failure of automotives is done using a traditional and old process known as Failure Mode and Effects Analysis (FMEA). Failure Mode and Effects Analysis takes into consideration the different events and effects that could make an automobile system to function inefficiently. Among the possible causes of failure, Failure Mode and Effects Analysis identify functional, process and design-related problems as the major causes of automotive failure. Traditionally, reliability of a system is taken to mean the probability of failure under specified operating conditions and circumstances. Typically, a look at failure mode avoidance and reliability of systems calls for proper understanding of several concepts. These include survival functions, mean times between failures and probabilistic failure rates. The concepts have relationships with a model to the causes of failure (Braunwart 2007, 20). The probable causes of failure of any automotive system are component reliability, environmental variability and material used. Specified operating environments are stipulated as a range agreed upon of estimated probability function and allowable conditions for variable or uncertain parameters. This is usually in a bid to quantize the model. The approach is suited for calculation of predicted failure rates once all the required data is availed. The general approach emphasizes reliability analysis. Failure Mode Avoidance Approach (Early Intervention in Avoiding Automobile Design Failure) The framework presented above is a sound approach to understanding reliability in avoiding failure mode. However, there is the second alternative that has over time proved to be quite effective in improvement of reliability and reducing failure of new systems in their early development. Several changes in system designs that enhance system reliability do so by moving the physical failure modes. Research has shown that most significant improvements in system reliability has stemmed from this approach. Although the scheme can be integrated with probability theory, it does not necessarily require the probability theory to comprehend how the design changes cause their effects. There are claims that failure-mode avoidance approach leads to numerous improvements since there is minimum data requirement; just enough data to guide the engineers through the next improvement. This is especially so since the failure-avoidance mode is used in the early development stages of a system. The failure-mode avoidance approach has deep connection with physics of systems and is, therefore, tangible and real to mechanical engineers. This facilitates the need for creative insights for the concept design. Additionally, failure-mode avoidance approach of improving efficiency of systems has the advantage of reducing resilience of specified operating conditions. A set of specified operating conditions refer to the approximations that aids to guide concept selection. It is not reasonable and practical for mechanical engineers to define a complete set of conditions that a system design is likely to experience throughout its life cycle. Although the engineers can define an approximation of sets of conditions, they are surely likely to miss some crucial combinations of sets of conditions. Later on after the system design, some unanticipated sets of operating conditions may cause the system to cease working. In the event that this happens, it may be tempting for the responsible mechanical engineers to argue that the system did not fail since the conditions of operation were not set. They may even argue that the system was probably misused. It is paramount that engineers recognize the fact that nature does not care what they think the operating conditions are. Failure is any moment the system fails to function under the prevailing conditions. Some reliability engineers understand this concept quite well. Messages such as “Trouble Not Identified” warrantee returns in the auto industry, for instance, must not be assumed that a returned module which passes all the tests associated with the specifications of an engineer are perfect. Due to uncertainties that regard specified operating conditions, mechanical engineers argue that an efficient approach is to increase the set of conditions under which the system operates. They argue that this needs to be done as quickly as possible and consider the best economic viability that an institution can manage. This implies that the field engineers need not to spend too much time and energy predicting field reliability. On the contrary, they need to spend the same energy increasing the field reliability to reduce failure mode instances. Creative design work which leads to improvement of reliability of systems is a natural activity and consistent with failure-mode avoidance conception of system reliability. As noted before, failure-mode avoidance approach can have real advantages to system designs especially in the early stages of system development. In the long-run, systems such as technological designs and automobile industry could reap the highest benefits of the approach. Probability Theory may prove to be too quantitative for the approach in the early stages of system development. Probability density functions entail a high level of precision in modeling a design scenario that is often uncalled-for in the early design stages. The probabilistic view of reliability of the system becomes increasingly important as the project progresses. Analyzing reliability using probability theory is significant for component selection, management of field service operations and system validation. The rate of failure mode avoidance conception of reliability is highest for system architecting, concept design, technology strategy and for some other robust parameter design activities. All these activities need to be those done in the early phases of system design and improvement. Theory of Inventive Problem Solving (TRIZ/TIPS) One of the most important and related developments in the theories of improving durability and reliability of systems is the Theory of Inventive Problem Solving. Sometimes, the theory is abbreviated as TIPS or TRIZ. It was described by Alschuller in 1984 and has recently undergone several dynamics to include broader contexts of innovation as put forward by Clausing and Fay in 2004. The theory is based on thousands of patents that reveal patterns among inventive solutions. A crucial underlying hypothesis is that inventive woes can be seen as conflicts that are solvable using innovative solutions. This enabled several patents to be organized into helpful taxonomic groupings (Crip Design Conference 2009, 38). In addition, Theory of Inventive Problem Solving has also given rise to the development of software products that facilitate its use by professional practitioners in many fields including mechanical engineering field. However, it is praiseworthy to remember that even though several patents proclaim that their primary objective is robustness, they do not deliver new functions. On the contrary, they deliver a wider range of already existing functions. While TRIZ is crucial for the development of new functions and elimination of detrimental side effects, it does not support reliability innovations to the degree that is thought desirable. There is the need to analyze and seek novel patterns of innovative engineering designs and works (Crip Design Conference 2009, 38). Physics of Failure (PoF) Physics of Failure (PoF) is a development in the engineering field that is closely related to failure mode avoidance. The scheme that was developed at Computer Aided Life Cycle Engineering Electronic Products and Systems at the University of Maryland emphasizes the use of Physics-based model for prediction of reliability and designing systems for reliability (Jargen 2008, 19). The approach is extended to product development and accelerated life testing of engineering designs. Taguchi’s Philosophy of Developing Designs that never fail Another important development in the reliability engineering in relation to mechanical engineering is the robust parameter design developed by Genichi Taguchi in 1993 (Jargen 2012, 39). There is potentially large space of control factors and settings that always places the function at desired target value for any design concept. In the Robust Parameter Design, engineers explore the design space to find out the changes capable of making the system more robust. Engineers focus on keeping the performance of the mechanical systems at its best even as robustness improves. The method deploys the use of orthogonal arrays in exploring the design space. At the same time, compound noises or the outer space are used in exploration of the range of possible operating conditions. Other constraints such as the Signal to Noise Ratios are the measures of robustness of the system designs and guide the engineers to preferable extents of the control factors (Jargen 2012, 39). (Braunwart 2007, 40) While Taguchi’s viewpoint is consistent with dependability engineering that guarantee non-failure mode of system designs, he downplayed “goal post” approach that is inherent in forbearance limits and specifications (Diamond 2005, 92). The researcher’s concept of quality loss utility replaced the contemplation of process yields and fault rates with focus on reducing discrepancy then conducting adjustments to targets. He implored engineers to consciously render their designs to unforgiving conditions in the studies. Successful exposure of systems to harsh conditions in experiments preceding their complete design requires a transformation in the mechanical engineering association (United States & NASA 2009, 32). In auto industry, cars and other automotive devices need to go through sturdy tests in their design stages to make sure they can endure the toughest conditions in the actual world. While some vehicle designs are designed to endure bad roads, engineers hardly ever take the prospect to envisage the worst as they design the cars. This is the transformation that Taguchi claims is needed fast and energetically. He says that there is need to be a move from the manifestation of high performance based on high statistical assurance to aggressive augmentation followed by sufficient confirmation of the design systems (United States & NASA 2009, 32). Robust Parameter Design Robust Parameter Design is one of the most helpful developments in mechanical and systems engineering in the 20th century. The frameworks were responsible for the development of the automobile industry in Japan that became dominant in the 1970s. The methods were subsequently adopted in other regions outside Japan. The timing of the adoption of Robust Parameter Design in the West corresponded to the improvement in quality and competitiveness of automobile industry in Europe and North America. The design was a significant part of the rise of automobile industry in Japan and the response of to the competitive challenge that the industry elicited. Robust Design approaches have continuously and incessantly improved and refined and have continued to be active area of systems and mechanical engineering fields. (Braunwart 2007, 28) Operating Windows Method Operating Windows Method is the other approach that can be used to avoid failure mode in the automobile industry. The framework was developed and practiced in the 1970s at Xerox Corporation. Operating Windows refers to the set of conditions under which a system design functions without failure (Strutt & Hall 2009, 21). In the Operating Windows framework, reliability of a system is improved by making the Operating Windows wider. In a recent issue of Technimetrics, Clausing described the process in details. In brief, the essence of the approach is to increase the value of degree of Noise Factors do as to increase the Failure Rate (Strutt & Hall 2009, 21). In addition, Operating Windows method changes the value of the control factors to broaden the operating window at a fixed rate of failure. Using this approach to improve operations at Xerox could provide a leeway on the manner in which it could be applicable in automobile industry. The approach was used to improve reliability of the paper handling machines in Xerox Corporation. At Xerox, paper stacks were constructed and designed to deliberately produce a great magnitude of variation. The paper that was used varied in geometry, surface condition and weight. The corporation ensured that the paper stacks were the worst anyone could encounter in field use. They operated in conjunction with near-the-limit of the operating window. The papers brought out the highest failure rates that anyone could encounter. Failure rates were in the order of 1 in 10 instead of 1 in 10000 (Jargen 2012, 39). Using a similar methodology and approach in automotive industry, engineers will be able to discern the effect of changes in rate of failure with changes in control factors such as feed belt angles and materials used for automobile manufacture. Despite using failure rates as a measure of performance, Operating Windows method has consistencies with Taguchi’s quality philosophy. Since failure rates are vastly increased by application of aggressive noises, enhancements can be made rapidly. This is possible despite sacrifice of the ability to predict field reliability accurately. While the term “Operating Windows” could seem to be overemphasis on the goal post approach, there is stress on expansion of the actual physical limits. Customer specified limits are seen as irrelevant (Strutt & Hall 2009, 21). While retaining the benefits of Taguchi’s approaches, Operating Windows poses a little more advantages to the automobile industry. In the Operating Windows methods, the reliability of the systems designed are measured in physical terms using the size of the operating window. This method may be more preferable in measuring and providing a more abstract measure relating to quantities such as Signal to Noise Ratio (Diamond 2005, 92). For instance, the Operating Windows method could be used to double the rate of vehicle production rather than contemplate on the ways of reducing the SNR by 6 decibels. Cognitive psychology could be important for mechanical engineers in using this method to enhance efficiency and reliability of their designs. According to cognitive psychology, there is an advantage in maintaining a connection to physical quantities instead of probabilistic measures. A mental connection to logic and physics of the system design is even more important for the early stages of the system than its later, more advanced phases (Diamond 2005, 92). There are a number of strategies that could be used to improve robustness of automobile designs by mechanical engineers. The strategies considered in making the designs more robust rely on approaches that involve concept design rather than parameter design. These changes do not only on the dynamics of values of design parameters, but also addition of novel components and features. It also involves changes in the configuration of designs and creation of innovations. Four strategies are available for realization of enhanced robustness. Foremost, engineers need to relax a constraint limit on uncoupled control factor. Secondly, the engineers could use physics of failure in avoiding failure of designs and systems. Thirdly, mechanical engineers in the automobile industry could create two distinct operating modes for two varying demand conditions. Lastly, they could exploit the interdependence between the two operating window system variables created (Brown 2013, 32). Relaxing a constraint on limit on uncoupled control factor involves seeking new technologies and architectures to relax constraints when the operating window is not large enough. This happens when a system variable only affects one-sided failure modes. Engineers and designers can then take its value to constraint limit. The engineers need to exploit the physical mechanisms associated with an embryonic failure to offset the failure mode. This increases the size of the operating window. Employment of two different operating modes targets at increasing the size of an operating window in the event that it is not feasible to simultaneously avoid a two-sided failure mode owing to a wide range of noise values. In the event that there are dependencies among failure modes, engineers need to look for means to make the dependencies to counteract the impact of noise factors. Reliability and robustness needs to be included in the engineering decision dealing with design and concepts of system component in a way that feels natural for the engineers (Abramovici, 2013 pg 49). Emphasize is put to use more naturalistic and hence more understandable formulation of vagueness instead of probabilistic and more conceptual advance used in reliability production. The aim of this is to use the terms engineers are used to instead of quantitative terms to describe reliability properties and hence adjust the design of improved robustness. This is a physical distance to the failure mode for example the distance in millimeters thickness of a worn out tire. This method of thinking is of advantage to the early stages of system design and support a genuine proactive approach (United States & NASA 2009, 32). Conclusion From the discussion, it is evident that mechanical engineers in the automobile industry need to place a lot of emphases on reducing the failure of their designs in the early stages. It is not only time saving for mechanical engineers, but also economical for the designers and quality assurers. Whereas there are several ways of ensuring that there is failure mode avoidance in automobile design, Operating Windows Methods seem to provide the best way of ascertaining quality and robustness. With Taguchi’s philosophy of exposing systems to the worst possible conditions while experimenting, mechanical engineers and designers have a secure future in providing the most reliable, robust automobiles. Reference List UNITED STATES, & NASA SCIENTIFIC AND TECHNICAL INFORMATION FACILITY. (2009). Aeronautical engineering. Washington, D.C., Scientific and Technical Information Branch, National Aeronautics and Space Administration. STRUTT, J., & HALL P.L. (2009). Global vehicle reliability: prediction and optimization techniques. Bury St Edmunds, Professional Engineering Publications. MCGILL, S. (2007). Low back disorders. Leeds, Human Kinetics. JURGEN, R. K. (2010. Automotive electronics handbook. New York, NY [u.a.], McGraw-Hill. JURGEN, R. K. (2008). History of automotive electronics. Warrendale, PA, Society of Automotive Engineers, Inc. DIAMOND, J. M. (2011). Collapse how societies choose to fail or succeed. New York, Penguin Books. http://downloads.bclibrary.ca/ContentDetails.htm?ID=B6C4D39F-2CD5-41E8-ADA2-EA135A865630. CIRP DESIGN CONFERENCE, ABRAMOVICI, M., & STARK, R. (2013). Smart product engineering proceedings of the 23rd CIRP Design Conference, Bochum, Germany, March 11th-13th, 2013. Berlin, Springer. http://dx.doi.org/10.1007/978-3-642-30817-8. BROWN, B. (2013). Daring greatly: how the courage to be vulnerable transforms the way we live, love, parent and lead. BRAUNWART, P. R. (2007). Uncovering and avoiding failure modes in driveline and tire/wheel NVH using a computational meta-model. Thesis (S.M.)--Massachusetts Institute of Technology, System Design and Management Program, 2007 BIROLINI, A. (2007). Reliability engineering: theory and practice. Berlin, Springer. Read More