5 smart machine trends OEMs need to know
The last 10 years have brought about dramatic advances in technologies that OEMs would never have expected to affect their designs or the salability of their machines, much less impact business models and profits so substantially.
Smart machines require less human intervention for runtime and maintenance, improve overall availability and production efficiencies, integrate easily with business systems to ensure demand is met just in time and integrate tightly with supply chain management objectives and systems. These five smart machine trends can assist OEMs to create a foundation for improving machine intelligence and reshape business models for enhanced revenue streams and cost containment.
Working with automation vendors that innovate with these smart machine trends will provide OEMs assurance that their products will be competitive and improve their customer service longer term.
1. IIoT: Improving revenue and service margins
As ethernet chipsets have increased in processing capacity, the price has come down to a point where every industrial sensing or actuating device has inborn capability to communicate and process information. This forms the framework for IoT and it has created a generation of devices that can be reconfigured, monitored, diagnosed and potentially repaired using mobile and remote devices.
OEMs that leverage this technology can effectively deploy intelligent devices and give themselves a margin-saving advantage as this intelligence:
- provides real-time diagnostics and potentially predictive analysis
- yields real-time feedback on potential failure modes of the machine and deployment of spare parts more efficiently to mitigate unnecessary parts stores and cash flow
- delivers the foundation of intelligent machine parameters to accommodate shifts in consumer demand or quick turn retailer inventory requirements
- improves global competitiveness and potential new revenue streams as information is processed downstream.
2. Analytics become mainstream
Not long ago, analytics were the domain of big data players and supercomputer houses.
Today, analytics are available in small footprints and built directly into products, allowing fit-for-purpose analytics to relay critical information in real time. Many solutions now use small analytic engine models to provide immediate diagnostics and critical information to users.
This means that OEMs can more easily access and analyse relevant information with succinct reporting and dashboards to inform decision-making. This may include reporting of information to ensure any potential downtime is minimised or eliminated.
3. Remote monitoring through cloud services
As a way to reduce the expensive IT support and capital costs needed to process the abundance of data in their systems, more end users have embraced cloud-based services. As a result, security procedures have improved, and OEMs now have secure remote access to the data related to their machines and their output. OEMs have developed standard monitoring tools to alert their clients to anticipated mechanical or operator issues, safety concerns and production anomalies.
4. Machine learning
Smart machines take advantage of technology and aggregate the learnings from individual sensors and components into algorithms that mitigate downtime and provide prognostic and predictive diagnostics. They provide enhanced value to the end user through improved OEE and optimise availability. Further, as conditions on the machine change over time — due to mechanical degradation, product changeovers or operating conditions — these algorithms can auto-tune and auto-correct to retain performance and availability while providing diagnostic information and alarms to appropriate personnel.
OEMs can benefit from these developments, including by scaling down to control component levels in order to optimise OEE and efficiency for end users.
5. The rise of robotics
Forecasts suggest the number of industrial robots will rise exponentially for the next 10 years and it’s easy to see why. Robots can collaborate with human co-workers. They can perform highly repetitive and precise operations in dangerous environments. They have also become safer and more versatile as smart sensor technologies have advanced.
More material handling OEMs are considering robotics to be a critical part of their next-generation designs and look to specialised vendors to work closely with automation integration, information management and operator workflows to ensure optimised throughput and safety.
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