Mechanical failures in industrial equipment are typically linked to issues during the design phase, manufacturing, or operation and maintenance.
All of these instances, however, have something in common: these failures usually happen prematurely due to negligence in adhering to established prevention procedures, or due to a lack of proper methods and tools.
Therefore, it is imperative to incorporate methods for preventing failures at every stage of a machine’s lifecycle, from design to operation, as well as identifying these faults early on and acting based on automatic diagnostics. But before we dive into prevention techniques, we must first gain a better understanding about why these machine failures happen and how they affect equipment.
What Are Mechanical Failures?
Mechanical failures are closely linked to defects in material, manufacturing flaws, or design shortcomings. This can lead to various types of asset failures such as fractures, corrosion, premature wear due to alignment or balancing issues, among others.
Mechanical failures are also associated with the natural wear over time from asset usage. This typically happens due to wear on rotating parts and components such as bearings. As mentioned earlier, mechanical failures can also result from improper use of the asset and inadequate or lack of maintenance.
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The Importance of Failure Prevention
Investigating the causes of mechanical failures requires a deep understanding of the machines and the operational environment around them. It also calls for a correct comprehension of failure mechanisms and how to identify them in different applications.
Failure prevention is undeniably the most appropriate way to ensure general equipment reliability. In the context of prevention, it is crucial to understand the causes of mechanical failures.
And remember, there are four types of failures: hidden failure, potential failure, functional failure, and total failure. The focus of prevention is to anticipate these failures before they reach the final stage.
In the worst-case scenario, if total failure does happen (causing a full breakdown and production downtime), it is essential to conduct an analysis with preventive actions to prevent it from happening again.
Best Practices for Failure Prevention
One of the best ways to continuously implement prevention practices – be it before, during, or after the issue has happened – is by incorporating Failure Mode and Effects Analysis (FMEA), which involves three main factors:
- Failure modes
- Failure consequences
- Implications of the occurrence of failures
Parallel to this, it is important that industries carry out a consistent failure analysis process for problems that can somehow affect the operation. An increasingly popular strategy is that of investing in predictive maintenance techniques, especially those guided by condition monitoring.
Alongside FMEA, one of the best practices for preventing failures is the use of Reliability-Centered Maintenance (RCM) methodologies, which focuses exclusively on failure prevention by identifying the best maintenance practices for asset management.
Preventive Maintenance
When discussing effective strategies in preventing mechanical failures, preventive maintenance, or PMs, are the way to go. However, to have a successful PM strategy, it is essential to have appropriate and regularly updated maintenance scheduling.
Items and topics included in PM schedules must be as consistent as possible, and the focus should be on equipment with predictable wear due to usage over time. As part of the strategy, it’s crucial to assess machine criticality in order to prioritize high-criticality assets. This approach leads to greater accuracy in the development of equipment maintenance plans.
There are several important tools to think of when considering a preventive maintenance strategy, including:
- ABC criticality matrix to classify all assets
- Checklists and procedures to ensure thorough equipment inspections
- Well-developed and constantly updated predictive maintenance plan
- Constant inspection/calibration of measuring instruments
- Continuous improvement mindset
- PM schedules according to a 52-week calendar, and many others
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Equipment Reliability
To strive for machine reliability is to focus on the maintenance costs caused by unplanned production downtime. This also encompasses the cost of spare parts, repair equipment, man-hour rates, and warranty claim expenses.
To ensure failure prevention, it is necessary to apply engineering knowledge and specialized techniques. Working on asset reliability will consequently reduce the probability or frequency of failures. The aim is to identify and rectify the root causes of failures despite efforts to prevent them.
Asset Management
All failure prevention best practices covered in this article are embedded in asset management. This is clearly outlined in ISO 55001: asset management supports adding value to maintenance activities and machinery, and focuses on enhancing asset performance by engaging in methods and tools that decrease or eliminate the occurrence of failures.
Predictive Maintenance
An essential strategy in asset management is the use of predictive and prescriptive techniques that contribute to the prevention of mechanical failures. With these techniques, it’s possible to predict failures such as unbalance, misalignment, and mechanical looseness. Failures are predicted based on the symptoms they cause, such as overheating, noise, and/or vibration above acceptable limits.
To better understand the process, let’s use a bearing failure as an example. We have a failure cause (lack of lubrication), followed by a symptom (overheating and/or noise), and finally, the failure (broken bearing). The aim of predicting failures is to interrupt this process before it leads to functional or total failure. In order to stop this cycle, there are offline and online prediction techniques available for application, each with its specific characteristics.
An essential strategy in asset management is the use of predictive and prescriptive techniques that contribute to the prevention of mechanical failures. With these techniques, it’s possible to predict failures such as unbalance, misalignment, and mechanical looseness. Failures are predicted based on the symptoms they cause, such as overheating, noise, and/or vibration above acceptable limits.
To better understand the process, let’s use a bearing failure as an example. We have a failure cause (lack of lubrication), followed by a symptom (overheating and/or noise), and finally, the failure (broken bearing). The aim of predicting failures is to interrupt this process before it leads to functional or total failure. In order to stop this cycle, there are offline and online prediction techniques available for application, each with its specific characteristics.
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Cost Reduction and Efficiency
By using all means to act in the prevention of mechanical failures, the immediate result is the reduction of operational costs and increased efficiency in all manufacturing processes. Managing production and maintenance processes proactively to achieve the expected results will help prevent not only mechanical failures, but all types of machine problems.
