Smart Condition Monitoring aids pharmaceutical manufacturers

15th June 2017
Source: Mitsubishi
Posted By : Anna Flockett
Smart Condition Monitoring aids pharmaceutical manufacturers

Boosting productivity and minimising down-time is the ultimate aim for pharmaceutical manufacturers. Frequently now with the goal of moving from batch production to continuous operation, Neal Welch, Life Science Sales Manager, Automation Systems Division at Mitsubishi Electric highlights the importance of smart condition monitoring technologies.

As a tightly regulated sector with huge financial incentives to keep production lines running, manufacturers in the pharmaceutical industry typically experience less unplanned down-time than those in other sectors. Indeed, pharmaceutical manufacturers as a whole can point to fewer hours of unscheduled down-time than the equally high value automotive industry, and fewer also than the similarly regulated food and beverage sector.

This has been the case for some time, surveys conducted as long ago as 2004 by down-time expert Don Fitchett highlighted not only this push for manufacturing excellence within pharmaceuticals, but also pointed out how extensively companies were tracking their down-time, with standardised metrics in place to report it. This was hardly surprising given that almost 90% of them cited that down-time was either extremely or very important.

However, monitoring unplanned down-time is not the same as preventing it. And the component failures or bottlenecks that are prime causes of down-time can also impact on production line performance and on product quality. Combined with availability, these three key performance indicators are at the heart of measuring Overall Equipment Effectiveness (OEE), as defined by the simple formula:

OEE = availability x performance x quality
Fast forward, then, to today, and statistics highlight an average OEE score within the pharmaceutical sector of 60-70%, some way short of the score of 85% that is generally considered as world class. So while the pharmaceutical sector is ahead of the curve in acknowledging and tracking its down-time, it would appear it is not yet truly on top of maximising availability and boosting line performance.

Pharmaceutical manufacturers are acutely aware that they need to increase machine availability and reduce unscheduled down-time in order to respond to global competition and minimise costs. But the traditional techniques for helping to predict down-time in order to manage maintenance and to help maximise reliable production have typically been either expensive – such as using out-sourcing experts to analyse machinery and interpret the results of complex algorithms – or highly subjective, relying on the experience of in-house engineers who are intimate with production lines and can ‘hear’ or ‘feel’ impending component failures.

The move to continuous production, from batch production is another trend in pharma manufacturing that is also creating an environment where production systems are even less tolerant of breakdowns or equipment variability. Traditionally a drug would be manufactured in stages, with lab tests carried out at each stage to confirm the attributes of the compound in production. Test regulations now however allow for real-time testing to be carried out on-machine during a continuous production process. So when the production process doesn’t stop, then reliability must be 100%.

Condition monitoring developments
In recent years, condition monitoring technologies have become mainstream – components that could be easily retrofitted to motors and rotating machinery to detect impending problems. From the outset, these opened up new possibilities for preventative maintenance, ensuring that components could be detected as nearing the end of their working lives and swapped out during scheduled maintenance. No longer would manufacturers be caught unawares by catastrophic failure. No longer would there be the problems of huge losses in productivity caused by down-time of a prime asset, with lost productivity running into perhaps tens of thousands of pounds, not to mention the emergency repair rates.

Today, though, we can go even further, with new generations of ‘smart’ technologies opening up the possibility not simply of preventative maintenance within pharmaceutical production, but of predictive maintenance. Key developments in sensor technology enable the continuous monitoring of many more machine parameters, cost-effectively, from large prime movers right down to smaller systems.

As an example, the Smart Condition Monitoring (SCM) solution from Mitsubishi Electric provides an integrated approach to monitoring the condition of individual assets, and enables a holistic approach to be taken to monitoring the asset health of the whole plant. These SCM systems can be operated continuously and can be relied upon to give a simple but effective warning prior to significant failure.

The ‘smart’ capability of the system and sensors comes from a combination of local, on-machine warnings – perhaps using the familiar traffic light system – and through having information from multiple sensors transferred over the plant network to PLCs and then on to HMIs, PCs or mobile devices for in-depth monitoring, advanced warning and more detailed analysis.

Maximising OEE
The SCM system supports a number of functions that aid in predictive maintenance, including bearing defect detection, imbalance detection, misalignment, temperature measurement, cavitation detection, phase failure recognition and resonance frequency detection. Linking multiple sensors into the control system enables the controller to analyse patterns of operation that are outside the norm, with a series of alarm conditions that provide alerts that attention is needed.

SCM doesn’t simply help to predict when a key component is nearing the end of its life, to enable replacement to be scheduled rather than being surprised by catastrophic failure. It also enables companies to see production trends, such as aspects of the line drifting out of tolerance. If unnoticed or left unchecked such trends could cause a stoppage resulting in the need for operator intervention; perhaps not catastrophic failure, but costly and accumulative of down-time nonetheless.

Even if such trends would not ultimately result in full process down-time, there is the possibility that they would eventually impact on product quality. Without an SCM implementation, the first a company may know about this is when a batch of products fails a critical QA inspection, meaning wasted product after all the value has been added.

Consequently we can see that smart condition monitoring techniques impact positively on all three aspects of the OEE equation (availability, performance and quality), helping pharmaceutical manufacturers in their drive towards world-class OEE scores.

Enabling continuous production
SCM can go further, by providing an essential tool to assist the pharmaceutical industry with the move from batch production to continuous production. This shift to continuous production requires increased running time between periods of scheduled maintenance, and is dependent upon the ability to reliably monitor the condition of the operation.

The SCM system addresses this requirement because, along with indicating a developing problem on a machine or line, it is also able to give meaningful detail about what the problem is and how serious it might be. And by providing a complete and holistic overview of the workings of the plant’s assets, it can also enable a model-based fault detection and identification system to be implemented, with an active fault diagnosis framework.

We can see, then, that SCM offers many benefits to the pharmaceutical sector. It provides reliable monitoring of individual machines and complete production lines, with intelligent process monitoring to deliver a full service built around machine diagnostics. Further, it offers easy installation and intuitive operation, with a system that is readily expandable. Using the ‘smart’ approach, condition monitoring can be easily integrated into the plant system architecture, starting with as much or as little is required, and growing the system as appropriate to provide the most comprehensive overview.

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