The Power of Data for Process Optimization
Think about your business. Each process is broken down into multiple stages and steps, like the teeth in a cog as it works its way around a machine. Optimizing your processes can ensure each step is not only necessary but also that they’re carried out efficiently.
Unnecessary steps, incorrect instructions, or use of unsuitable materials can cause process problems, so identifying and eliminating these is vital.
Optimizing centers on addressing those small issues individually, implementing changes, and monitoring performance. Working in an agile manner like this means you can:
- Bring about changes quickly
- Focus on one specific issue
- Monitor performance
- Quickly revert changes
- Reduce downtime
But how do you identify these problems and required changes? That’s where Henkel and data comes into play. Most companies have the ability to gather data, but it’s knowing what to do with it, and how to use it to your advantage, that can cause a challenge.
Data-driven methods for predictive maintenance optimization are all about empowerment and having access to actionable insights, such as equipment downtime analysis tools. In maintenance terms, failure data analysis can help you identify trends, spot potential breakdowns, and quickly eliminate these to ensure the continual optimal operation of your manufacturing plant.
Data Collection in MRO
Data analytics tools allow you to quickly review large data sets to establish associations, trends, and patterns within your maintenance and repair processes.
If you’re not already using analytics software for maintenance and repair processes, you could get left behind. More than 75% of businesses invest over $1 million a year in such Big Data initiatives3. You can use data to gather intelligent, actionable insights that give you an advantage in:
- Spotting problems before they are exacerbated
- Identifying trends to inform better ways of working
- Making more impactful decisions
- Reducing overall operational costs
In maintenance and repair, one of the biggest data analysis advances in recent years has been the emergence of condition monitoring. Accessing real-time data that lays out the condition of machinery and component parts can help:
- Identify issues early
- Carry out maintenance before a breakdown
- Increase operational uptime
Condition monitoring forms part of a predictive maintenance plan for many organizations. With the increasing use of sensors, smart machinery, and technology, extracting accurate information about the expected lifespan of specific parts and parameters to instantly analyze their condition is easier than ever.
Condition monitoring can assess numerous parameters, including4:
- Revolutions per minute (RPM)
Speed increasing or decreasing can indicate a change to operating conditions that may require intervention. For mixers and pumps especially, a change in viscosity can affect performance and may highlight an issue that needs attention, providing additional health insights for the asset.
Depending on the equipment being analyzed, this insightful data allows you to assess if parts are operating at a safe and efficient level. If they’re not, you can take action to analyze what the issue is and fix it before it escalates.
You can use ongoing monitoring of your machinery to predict trends within your operation. Business and industries that use data analytics collect data that can allow them to do this, but knowing how to use it to your advantage can make all the difference.
Certain parts, components, and machinery will face wear over time, and many parameters assessed via condition monitoring can highlight this in advance, estimating the remaining lifespan of that part.
Having access to this data allows you to look forward, planning when you might need to replace or fix the component in question. It can also make it easier to ensure you have essential products like threadlockers, thread sealants, and gasketing solutions when you need them, as well as booking time with specialized engineers, minimizing the time your machinery needs to be out of action.
Use predictive trends to anticipate failures before they happen. This can help reduce downtime through both identifying faults and arranging repairs. This real-time downtime analysis reporting can also be going on in the background without impacting your processes as a whole.
Reducing Productivity Drops
Common fault areas within your processes lead to downtime. These include both static and rotating parts, where mechanical loosening and misalignment can cause faults, downtime, and productivity loss.
By focusing on critical downtime analysis data points within pumps, electric motors, static pipes, and flanges, you can more efficiently identify issues within key problem areas.
Many operations already monitor things like pressure and flow, but with Henkel’s analytical services, we work with you to expand these critical data points to provide a more comprehensive analysis of your processes.
Optimizing Maintenance Processes
Data can help you make better informed decisions when it comes to routine maintenance. Previously, with both preventive and predictive maintenance optimization models, you might change fluids that keep machines lubricated and replace parts that become worn at set times. Similar to changing oil in a car, the maintenance is carried out at an agreed interval regardless of the part’s condition.
Industry 4.0 enables additional data gathering that provide an accurate insight into parts, components and fluids at a specific time. This can highlight if there’s still life in such components, meaning their use can be extended to save you time and maintenance costs for new parts and labor, reducing planned downtime.
These insights can also be applied to identify any parts, components or fluids that are closer to their end of life sooner than anticipated. Here, data software informs you when maintenance should be brought forward, avoiding a breakdown, unplanned downtime and the associated costs. In this way, Industry 4.0 helps enhance efficiencies in your maintenance tasks and routines.
Making Better and More Informed Decisions
Businesses succeed and fail on the strength of decisions taken by their people. Whether on the production line or in the boardroom, bad decisions can be costly. Make the right decisions with the help of your data.
Processes are central to high-level decision-making. Using Big Data to influence these processes could help improve performance by 26%5. Data analytics can also pinpoint the most valuable information in huge data sets to help you make better decisions.
No matter your industry, at Henkel, we can provide a comprehensive analysis of your manufacturing process to identify problems and recommend effective maintenance and repair solutions.
We’ll work closely with you to deliver timely and accurate sample analyses and downtime reports so you can make changes fast and reap the benefits of optimizing your plant maintenance with data.
Discover more about the power of Henkel services and book a consultation today.