The factory of the future, in which all conceivable devices are connected with their intelligence and autonomy and each plant process is constantly optimized through sophisticated real-time analytics, has long been the utopia of industrial automation.

It promises to unlock unseen levels of productivity and efficiency while removing the need for humans to carry out many of the more repetitive or labor-intensive tasks required, potentially saving organizations vast amounts of money and time.

However, the idea of the smart factory is not yet a reality for all. It takes time, planning, and often significant investment to radically modernize an entire plant from the ground up.

Unfortunately, this can be beyond the reach of all but the largest and most well-resourced organizations. Rebuilding complex processes from scratch is often not affordable or feasible, while legacy equipment, which may still have plenty of life left in it, can be expensive to replace.

As well as requiring the latest technologies, a smart factory also requires a rethink in structure and culture to overcome compartmentalization, organizational silos, and work habits that are no longer conducive to operational efficiency in the digital age.

Industry 4.0

In many cases, a radical rebuild is not necessary to start embracing the benefits of Industry 4.0. Incremental improvements, such as adding condition monitoring capabilities to existing equipment can unlock a vast potential for savings across the areas of efficiency, productivity, and reliability throughout the plant.

The term “Industry 4.0” is relatively new, originating in Germany in 2011 and becoming widely popularised by 2015. Whilst it means different things to different people, in general, it refers to the widespread adoption of new technological breakthroughs in robotics, AI, nanotechnology, quantum computing, and other technological breakthroughs.

Crucially, it offers greater visibility over running processes. Digital connectivity provides real-time or near-real-time insight into asset health, allowing maintenance teams to focus their efforts where needed and avoid expending resources unnecessarily. It can also prevent large amounts of downtime by flagging and fixing potential issues before they turn into failures.

You can implement condition monitoring without substantially rethinking existing processes, and you can roll it out on a much smaller scale to embrace the efficiency, reliability, and productivity savings promised by Industry 4.0, at a fraction of the cost.

Sensors Are Getting Smarter

Attach sensors to legacy equipment to measure health, tracking metrics like vibration, temperature, and power signatures for a comprehensive view, avoiding manual component inspection.

Measuring and analyzing assets remotely improves plant safety in hazardous areas without endangering personnel.

Capturing this data is one thing, but using it to generate useful insights requires a more holistic approach. Many machines and closed-loop systems already have the provision for condition monitoring and analysis, but to put that data into context we need to transfer it into a higher-level operational framework, reaching beyond manufacturing execution systems (MES) and into enterprise asset management (EAM).

Operations aim to enhance machine health visibility by analyzing current and historical data for insights into plant maintenance and reliability.

This shift from reactive maintenance to predictive maintenance involves carrying out maintenance specifically when and where it is needed. This in turn reduces the risk of maintenance activities introducing new problems that were previously not there.

Connectivity is Key

Data connectivity, like the flow of data from the monitor to maintenance software systems, is crucial for effective condition monitoring plans.

Analytics solutions are only as sophisticated as the data back end that underpins them. In other words, the system is only as good as the data that goes into it, while context is also critical.

Real-time condition data may not reveal an asset’s last service, actions taken, or upcoming maintenance schedules. It won’t display the asset’s failure history, needed parts for repairs, or their availability.

Digital connectivity can help to provide this context. Sensors on their own are useful but limited in what they can achieve in providing useful insights across operations. Plugging the data into higher-level control systems unlocks the real efficiency gains. Optimize systems to reduce alarms and deliver pertinent data promptly for informed decision-making.

Once the system collects the relevant data, it needs to funnel it into a platform where it can be aggregated and integrated with data from other systems. It enables trend analysis to predict and address issues before they escalate into failures.

Measuring extensively and extracting data from assets enables analysis of various variables, revealing new insights and preventing unforeseen issues.

Condition Monitoring Systems

Effective condition monitoring systems should include:

1. Data connectivity: Data is combined into a usable state and stored in an accessible location.
2. System connectivity: Integration of asset health data with related systems used by maintenance teams.
3. Team connectivity: All personnel have access to asset information, which allows for more efficient maintenance actions.

Looking Ahead

For many facilities, the factory of the future is not something that happens overnight. Ripping out and rebuilding entire systems is often not feasible, particularly for smaller enterprises. However, the technological building blocks required to unlock some of the benefits of the smart factory are already widely available.

Sensors are coming down in price all the time and becoming more versatile and reliable, while improvements in networks and processing power are making sophisticated condition monitoring more accessible to a wider cohort of businesses that previously lacked the resources to explore it.

In effect, condition monitoring enables companies to start small, and grow digital capabilities gradually in a more manageable and cost-effective way. This also allows you to prioritize assets in a way that provides the best return on investment.

From there, you can expand condition monitoring programs to other operations, and before you know it, much of the plant will be connected.

From a practical perspective, this will enable an immediate improvement in maintenance efficiency, while in the long term it can help to uncover and solve chronic or previously undetected issues and inefficiencies for better productivity and profitability in the future.

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• Source: https://www.iotforall.com/condition-monitoring-the-possibilities-of-industry-4-0