Zdzislaw H. Klim

Cutting tool reliability analysis for variable feed milling of 17-4PH stainless steel

Variable feed machining has recently been proposed as a significant method to improve cutting tool life particularly for hard and diffucult to machine materials. This method, which is easy to apply in industry, has been shown to improve tool life in the order of 40% in certain cases. This paper presents a reliability model for the quantitative study of the effect of feed variation on tool wear and tool life. To better compare processes with two different wear modes, a reliability model taking simultaneously into account both flank and face wear has been developed. With this model, which is based on experiments, the tool life for the constant and variable feed cases was calculated from the reliability function. The mean time to failure, obtained from the reliability function, provides an accurate evaluation for any probabilistic distribution. The proposed method is therefore a general approach that can be used for analyzing cutting tool life under any conditions and for any equipment and material.

Integrated Safety Management System

The Safety Management System requires a structured Risk Management Process to be effective. In the technical fields where numerous potentially catastrophic risks exist, processes and procedures need to account not only for the hardware random failures but also of human errors. The technology has progressed to the point where the predominant safety risks are not so much the machine failures but that of the human interaction. Accidents are rarely the result of a single cause but of a number of latent contributing factors that when combined result in the accident. In the Aerospace industry, the operational risk to the fleet is assessed by the manufacturer and the operator independently and is used in safety and/or regulatory decision-making. For the manufacturer, the risk assessment is a philosophy whereby risk of a potential or actual occurrence is evaluated in comparison to the event analyzed in the system safety assessment or structural analysis performed for certification of the product. The resulting safety decision-making process involves integration of the probabilistic risk assessment, deterministic and severity perception elements such that the decisions made leads to corrective or preventative actions. The evaluations of the human factors elements are subjectively assessed based on individual experience based criteria and are difficult to integrate into the safety decision. The risk assessment is viewed as the process that records all these factors as the basis for the safety decision and prioritization of the corrective actions. In the Nuclear industry a risk-informed approach to safety and/or regulatory decision-making represents a philosophy whereby risk insights are considered together with other factors, including good engineering practice and experience, to establish the design requirements and operational issues commensurate with their importance to public health and safety. A standard risk-based approach to safety and/or regulatory decision-making is one in which a decision is based solely on the numerical results of a risk assessment. Quantitative risk analyses are important inputs to decision making, but they do not constitute an adequate or sufficient base of information for addressing the complex issues that face the nuclear power industry. For that reason such analyses are only one of the many contributing inputs to a comprehensive risk-informed decision making process. Risk-informed decision making involves integration of probabilistic, deterministic and non-quantifiable elements such that, overall, the decisions made lead to a resolution of the issue being considered that is commensurate with its risksignificance and is better to that likely to be reached if any approach is used in isolation. This paper intends to compare the Risk Management methodologies and procedures used in the Aerospace and Nuclear industries to highlight similarities and differences. The learning from these differences may then identify potential improvements to either methodology.