In industry, it is very difficult if not impossible to avoid downtime due to equipment failure. For all the best maintenance approaches that are out there, predicting and preventing failure cannot be regarded as a science. From traditional “time” based maintenance through to complex condition based monitoring and predictive techniques, downtime can be reduced, but time will come when replacement is unavoidable. This is true in all types of industry. All material assets have a life expectancy and the duration will always be dependent on multiple factors.
Predicting the right time to replace an asset in order to maximize its life without compromising its effectiveness can be determined in two ways.
- Mathematical modeling using complex algorithms
- Applied direct knowledge and experience
ALMS is designed using the latter approach. It has been developed on the back of nearly 40 years of manufacturing experience in the life science sector. It has drawn on this experience to design a model that does not predict failure but instead assesses the condition of equipment and in so doing provides a consistent method of scoring. It is this consistency that is so important to the model and gives it its validity.
Within the model, we talk about Robustness and Risk. It is important that we understand these two terms before we go any further.
From the dictionary definition robustness is the “ability of a system or component (in its current state) to perform as expected under erroneous, stressful, or unexpected inputs or conditions”
ALMS takes the definition and expands on it in order to provide a relative value for scoring. Relative in the sense that it is consistent across all assessments and is based on relevant scoring criteria.
Robustness in this instance should be thought of as an asset evaluated condition with respect to its current state and the influence of the “environment”
Risk is by definition “A situation involving exposure to danger”
Risk in the ALMS context is a term used to express the consequence of failure to perform dependent on the robustness of the asset and including three other variables. It must be made clear that “Risk” using the ALMS definition is not simply the “risk of failure” of the asset but more so the consequential risk of failure.
From this understanding it is obvious that there is a relationship between robustness and risk but that the relationship depends on other factors such as the assets criticality, spares holding etc.
ALMS is a “Lean” approach to assessment. There is no clipboard and pencil scoring and transposing for analysis and write-up. The ALMS advantage is that of efficient electronic tablet data capture and calculation. An export function to standard workbook format aids in the analysis and report generation. From a customer or client perspective it is business efficient by reducing duplication of effort.
What are the components of assessment?
The ALMS system records specific criteria associated with “robustness” both from an external influence as well as the perceived ability of the asset to withstand the passage of time. The criteria can be loosely classed as either internal or external influences.
There are ten assessment points. They were created during development of the product and were evaluated as to their degree of influence within the assessment process. It is only natural to expect that not all influences will be directly proportional to each other and hence a weighting system was introduced.
For more information on the ALMS product and its design get in contact.