Process Failure Risk Analysis

Our failure risk analysis and opportunity method and iterative software tool, as part of our New Product Process Innovation (NPPI) Tool Library, promotes systematic collaboration and team-oriented engineering thinking when a new pharmaceutical manufacturing system process and/or product are developed. (We call it opportunity method too, since most risks, if not all, offer new opportunities for innovation.) It is based on our generic process failure risk analysis method that could be apphed to literally any process that involves risk—and innovation is a very risky process. 

FIGURE 7 The process failure risk analysis (PFRA) tool is an analytical and computational tool using rule bases for evaluating process risks. It is an ideal method and tool for reducing costly failures. (For more about this software tool, see http //www.cimwareukandusa.com. 

As it was mentioned the operator performance is influenced by the human and organizational factors. If they are properly shaped can contribute significantly to mitigating the human error probability (HEP) and failure events that result in decreasing the risk related to accidents scenarios identified in the process of risk analysis. 

Smith, J. B., Predicting Future Failure Risk with Weibull Analysis, First International Conference on Improving Reliability in Petroleum Refineries and Chemical Plants and Natural Gas Plants, Organized by Gulf Publishing Co. and Hydrocarbon Processing, Houston, TX, November, 1992. 

The other main application area for predictive error analysis is in chemical process quantitative risk assessment (CPQRA) as a means of identifying human errors with significant risk consequences. In most cases, the generation of error modes in CPQRA is a somewhat unsystematic process, since it only considers errors that involve the failure to perform some pre-specified function, usually in an emergency (e.g., responding to an alarm within a time interval). The fact that errors of commission can arise as a result of diagnostic failures, or that poor interface design or procedures can also induce errors is rarely considered as part of CPQRA. However, this may be due to the fact that HEA techniques are not widely known in the chemical industry. The application of error analysis in CPQRA will be discussed further in Chapter 5. 

When using failure rate data for a CPQRA, the ideal situation is to have valid historical data from the identical equipment in the same application. In most cases, plant-specific data are unavailable or may carry a level of confidence that is too low to allow those data to be used without corroborating data. Risk analysts often overcome these problems by using generic failure rate data as surrogates for or supplements to plant-specific data. Because of the uncertainties inherent in risk analysis methodology, generic failure rate data are frequently adequate to identify the major risk contributors in a process or plant. 

Several qualitative approaches can be used to identify hazardous reaction scenarios, including process hazard analysis, checklists, chemical interaction matrices, and an experience-based review. CCPS (1995a p. 176) describes nine hazard evaluation procedures that can be used to identify hazardous reaction scenarios-checklists, Dow fire and explosion indices, preliminary hazard analysis, what-if analysis, failure modes and effects analysis (FMEA), HAZOP study, fault tree analysis, human error analysis, and quantitative risk analysis. 

Fault tree analysis is based on a graphical, logical description of the failure mechanisms of a system. Before construction of a fault tree can begin, a specific definition of the top event is required for example the release of propylene from a refrigeration system. A detailed understanding of the operation of the system, its component parts, and the role of operators and possible human errors is required. Refer to Guidelines for Hazard Evaluation (CCPS, 1992) and Guidelines for Chemical Process Quantitative Risk Assessment (CCPS, 2000). 

As a result of the AIC s efforts, we now have a process for investigating accidents in which we construct an event tree for each incident. The tree is quite similar to a fault tree from the quantitative risk analysis discipline, except that in the investigations we often sacrifice some structural rigor to get the most results in a reasonable time. Basically, the process uses a team to reconstruct the chronology of the incident and to construct the event tree. We try to include those who are most familiar with what actually happened, including the injured person(s) if any. We use the same basic method to investigate process failures, spills, injuries, or any other system failures. Emphasizing the system aspects of the failure removes much of... 

Hazard and risk analysis is a vast subject by itself and is extensively covered in the literature [22]. In order to plan to avoid accidental hazards, the hazard potential must be evaluated. Many new methods and techniques have been developed to assess and evaluate potential hazards, employing chemical technology and reliability engineering. These can be deduced from Fault Tree Analysis or Failure Mode Analysis [23], In these techniques, the plant and process hazard potentials are foreseen and rectified as far as possible. Some techniques such as Hazards and operability (HAZOP) studies and Hazard Analysis (HAZAN) have recently been developed to deal with the assessment of hazard potentials [24]. It must be borne in mind that HAZOP and HAZAN studies should be properly viewed not as ends in themselves but as valuable contributors to the overall task of risk management... 

Risk management should be central to the planning, budgeting, and acquisition process. Failure to analyze and manage the inherent risk in all capital asset acquisitions may contribute to cost overruns, schedule shortfalls, and acquisitions that fail to perform as expected. For each major capital project, a risk analysis that includes how risks will be isolated, minimized, monitored, and controlled may help prevent these problems. 

An undetected failure in a system as non-identified hazards during risk analysis, or if insufficient measures are taken, or if an initially well-designed process gradually deviates from its design due to changes or lack of maintenance. 

The deviation scenarios found in the previous step of the risk analysis must be assessed in terms of risk, which consists of assigning a level of severity and probability of occurrence to each scenario. This assessment is qualitative or semi-quantitative, but rarely quantitative, since a quantitative assessment requires a statistical database on failure frequency, which is difficult to obtain for the fine chemicals industry with such a huge diversity of processes. The severity is clearly linked to the consequences of the scenario or to the extent of possible damage. It may be assessed using different points of view, such as the impact on humans, the environment, property, the business continuity, or the company s reputation. Table 1.4 gives an example of such a set of criteria. In order to allow for a correct assessment, it is essential to describe the scenarios with all their consequences. This is often a demanding task for the team, which must interpret the available data in order to work out the consequences of a scenario, together with its chain of events. 

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