Mitsubishi Electric servos have built-in analytics that monitor performance of the attached load and operate in a continuous tuning mode to ensure optimum performance at all times.
- Analytics become mainstream Not long ago, analytics were the domain of Big Data players and super computer houses. While these players still hold relevance to major users and producers, many sets of information require more immediacy and cannot tolerate the latency of uploading and processing these players require. Analytics are now available in small footprints and are built directly into products, allowing fit for purpose analytics to relay critical behaviors in real time. Many vendors are now pursuing the small analytic engine model to provide immediate diagnostics and repair information to the user as well as report back to the OEM so that any potential downtime is minimized or eliminated.
- Using analytic data from a fleet of installed machines provides the OEM aggregated feedback on failure analysis, vendor performance, and customer
utilization. It also provides a window into the machines actual utilization so that improvements and evolution, or remote upgrades become revenue
enhancements for the future.
Mobile technology expands and empowers manufacturing operators, managers and supervisors to make timely decisions no matter where they are.
- Remote monitoring through cloud services
More end users have adopted cloud based services as a means to contain the costly IT support and capital expense required to process the proliferation of data in their systems. As a result, security practices have matured and OEMs can have access to their machine data and related production information through judicious accessibility. OEMs have created standard monitoring capabilities to advise their customers of impending mechanical or operator issues, safety concerns, and production anomalies. Typically control vendors are providing preconfigured diagnostic screens on their HMIs in order to advise operators of fault or alarm conditions, and in parallel, advise the OEM of the need for parts or service.
- OEMs can gain an added benefit in using remote monitoring services to adapt their business models. For example, knowing the behaviors, attributes and the utilization characteristics of a fleet of machines can provide useful insight in the evolution of machine designs, upgrades for users, and off site remote services such as maintenance monitoring and repair requests. Similarly, fleet monitoring provides a window to part failures, spares requirements, and analysis of inventories to ensure only required spares are inventoried locally – reducing carrying costs and improving delivery times.
Machine learning diagnostics compensate for vibration and friction. This information is displayed on GOT operator terminals and remotely.
- Machine learning
Smart Machines take advantage of vendor technologies and aggregate the learnings from individual sensors and components into algorithms
that mitigate downtime and provide prognostic and predictive diagnostics. These machines provide enhanced value to the end user through improved OEE and optimized availability. Further, as conditions on the machine change over time – due to mechanical degradation, product changeovers or operating conditions, these algorithms auto-tune and auto-correct to retain performance and availability while providing diagnostic information, and alarms to appropriate personnel.
The ability of individual components to monitor and correct aberrant behaviors is critical to running production at full speed with less operator
intervention, and less lost production and downtime.
Mitsubishi Pak/iQ offerings include integrated robotics, servo and PLC programming from a single software package, modular code templates and mechatronics estimation tools.
- The rise of robotics
Forecasts call for the number of industrial robots to rise exponentially for the next 10 years and its easy to see why. As mentioned above, human resource constraints, technical sophistication and faster machine speeds predicate assistance from robotic elements. In some cases, robotics augment and collaborate with human co-workers, and in others, perform highly repetitive and precise operations in dangerous environments. Robotics have become safer and more versatile as smart sensor technologies have advanced. More machine builders consider robotics a critical part of their next generation designs and look to specialized vendors to work closely with automation integration, information management, and operator workflows to ensure optimized production and safety. Importantly, the automation system and robotic system should be tightly coupled in programming and configuration in order to maximize engineering efficiency and longer-term maintenance issue.
Bringing it all together
Smart Machines will require less human intervention for runtime and maintenance, improve overall availability and production efficiencies, and integrate
easily with business systems to ensure demand is met just in time, and is integrated tightly with supply chain management objectives and systems. Users
faced with increasing margin pressures, operator skill challenges, and the impact of immediate demand requirements are increasingly expecting
integrated smart machines that can operate autonomously while communicating upstream to ensure demand is met, quality is guaranteed, and
losses are minimized. Working with automation vendors that innovate in these Smart Machine technologies will provide OEMs assurance that their
designs will be competitive and improve their customer service longer term.