Among the amazing benefits of the Internet of Things has been its ability to generate innovative predictive maintenance solutions. These allow you to determine the condition of equipment and forecast when maintenance should be performed. That reduces what we might call the “problems of the unexpected.”
All good, right? Yes, for sure, but companies need to think bigger than that.
While predictive maintenance solutions offer great benefits on their own accord, it is essential to take a more holistic perspective when adopting predictive maintenance solutions for an even bigger impact.
Predictive maintenance is not an island unto itself. It has strong interlinkages with Production, Inventory Management, Quality and Customer Service and correspondingly delivers very positive downstream impacts on these functions. A predictive maintenance program implemented well can also significantly reduce quality issues, improve production scheduling accuracy, reduce the need for on-hand spare parts and enhance employee safety.
At Hitachi, we take an all-encompassing approach to implementing our predictive maintenance solution. Some of the key downstream impacts of a well-orchestrated predictive maintenance program include:
Often, quality issues are directly related to the degradation of equipment. By ensuring that a machine receives in-time maintenance prior to failure, your customers will see fewer quality issues. The machine learning models built into the predictive maintenance solution can identify equipment that is starting to deteriorate and notify maintenance personnel in the early stages of degradation for in-time maintenance scheduling and avoiding major quality impacts.
Enhance production scheduling
Predictive maintenance solutions can help to improve production scheduling. With accurate information about when an asset will or won’t be available for use, you can create smarter, data-driven production plans. You can:
- Compartmentalize production to avoid risk of increased WIP.
- Plan apt time windows for maintenance and reduce planned maintenance time.
- Reduce risk with alternative production pathways.
Reduce spare parts inventory
When critical spare parts fail, they can cause production lines to stop, creating unplanned downtime and production loss. Many of these parts are candidates for IoT and predictive analytics, where you can track, monitor and forecast failure, and determine when a part’s life expectancy is critical. The related data—such as the age of the component, number of repairs, failures, current condition and expected end of life—is also valuable as part of your planning process for spare parts and capex forecasts.
Enhance employee safety
Employee safety is an ongoing concern for manufacturing companies. When you implement a predictive maintenance solution, you gain actionable insights into maintenance needs that can reduce the risk of employee injury related to machine malfunctions. Employee safety can be further enhanced when blending data from a predictive maintenance solution with OSHA-certified wearables to support regulatory compliance. The data collected from the wearables serves as a wellness monitor for specific kinds of injuries, such as knee, shoulder and lower back etc. In essence, this helps achieve significant improvements on the employee safety metric in turn reducing workers’ compensation claims.
Why Hitachi for predictive maintenance and analytics?
Hitachi has more than 100 years of experience in the manufacturing industry as well as over half a century of experience developing IT solutions. We have a strong track record of solving operational challenges with solutions that combine the latest cutting-edge technology, including IoT and AI-driven data analytics.
Our team of data scientists, researchers and industry thought leaders at the Hitachi Center for Social Innovation has developed a suite of predictive maintenance technologies and solutions for the manufacturing, transportation, oil and gas, mining and healthcare industries.
Our predictive maintenance suite provides solutions for the manufacturing, transportation, oil and gas, mining and healthcare industries. It leverages our overall expertise spanning across IoT platform skills, maintenance domain know-how, operational technology competence across diverse verticals, and rich knowledge of diverse asset classes topped with very strong analytical capabilities on machine learning and data science.
While the most evident cost savings result from reduced downtime, look for a solution that delivers downstream process improvements with significant and ongoing financial benefits.