Page 21 - EngineerIT October 2021

AUTOMATION AND CONTROL

monitored, diagnosed, and potentially repaired using mobile and requirements and analysis of inventories to ensure only required
remote devices. OEMs who effectively deploy intelligent devices spares are inventoried locally – reducing carrying costs and
inherently give themselves a margin-saving advantage as this improving delivery times
intelligence does several things for them:
• Provides real time diagnostics and potentially predictive 4. Machine learning
analysis Smart machines take advantage of vendor technologies and
• Provides real time feedback on potential failure modes of the aggregate the learnings from individual sensors and components
machine and deployment of spare parts – more efficiently to into algorithms that mitigate downtime, providing prognostic and
mitigate unnecessary parts stores and cash flow predictive diagnostics. These machines give enhanced value to
• Provides the foundation of intelligent machine parameters the end user through improved OEE and optimised availability.
to accommodate shifts in consumer demand or quick turn Further, as conditions on the machine change over time – due
retailer inventory requirements to mechanical degradation, product changeovers or operating
• Improves global competitiveness and potential new revenue conditions, these algorithms auto- tune and auto-correct to
streams as information is processed downstream retain performance and availability while providing diagnostic
information and alarms to appropriate personnel.
2. Analytics become mainstream The ability of individual components to monitor and correct
Not long ago, analytics were the domain of Big Data players and aberrant behaviours is critical to running production at full speed
super computer houses. While these players still hold relevance with less operator intervention and less lost production and
to major users and producers, many sets of information require downtime.
more immediacy and cannot tolerate the latency of uploading and When dealing with high-speed sortation, warehouse
processing these players require. Analytics are now available in operations and ASRS systems, precision under variable
small footprints and are built directly into products, allowing fit for load and mechanical conditions is critical to cycle times and
purpose analytics to relay critical behaviours in real time. Many delivery performance. Machine learning, scaled down to
vendors are now pursuing the small analytic engine model to control component levels provide optimised Overall Equipment
provide immediate diagnostics and repair information to the user Effectiveness (OEE) and efficiency.
as well as report back to the OEM so that any potential downtime
is minimised if not eliminated. 5. The rise of robotics
Using analytic data from a fleet of installed machines provides Forecasts call for the number of industrial robots to rise
the OEM aggregated feedback on failure analysis, vendor exponentially for the next 10 years and it’s easy to see why.
performance and customer utilisation. It also provides a window As mentioned above, human resource constraints, technical
into the machines’ actual utilisation so that improvements and sophistication and faster sortation and handling speeds predicate
evolution, or remote upgrades, become revenue enhancements assistance from robotic elements. In some cases, robotics
for the future. augment and collaborate with human co-workers, and in others,
For material handling applications, on board analytics can be perform highly repetitive and precise operations in dangerous
helpful in maintaining runtime and improving cycle times. Utilisng environments. Robotics have become safer and more versatile
on board analytics in real time provides high response tracking as smart sensor technologies have advanced. More material
and sorting, adaptive tuning to accommodate longer run time in handling OEMs consider robotics a critical part of their next
suboptimal conditions and algorithms designed to prevent sway generation designs and look to specialised vendors to work
or vibration induced by loads or mechanical deterioration. closely with automation integration, information management and
operator workflows to ensure optimized throughput and safety.
3. Remote monitoring through cloud services Importantly, the automation system and robotic system should
More end users have adopted cloud-based services to contain be tightly coupled in programming and configuration to maximize
the costly IT support and capital expense required to process engineering efficiency and longer-term maintenance issues.
the proliferation of data in their systems. As a result, security
practices have matured, and OEMs can have access to their Bringing it all together
machine data and related production information through Smart machines will require less human intervention for runtime
judicious accessibility. OEMs have created standard monitoring and maintenance, improve overall availability and production
capabilities to advise their customers of impending mechanical efficiencies, and integrate easily with business systems to ensure
or operator issues, safety concerns and production anomalies. demand is met just in time, and is integrated tightly with supply
Typically control vendors are providing preconfigured diagnostic chain management objectives and systems. Users faced with
screens on their HMIs to advise operators of fault or alarm increasing margin pressures, operator skill challenges, and the
conditions and, in parallel, advise the OEM of the need for parts impact of immediate demand requirements are increasingly
or service. expecting integrated smart machines to ensure demand is met,
OEMs can gain an added benefit in using remote monitoring quality is guaranteed and losses are minimized. Working with
services to adapt their business models. For example, knowing automation vendors that innovate with these smart machine
the behaviours, attributes and the utilisation characteristics of a technologies will provide OEMs assurance that their designs will
fleet of machines can provide useful insight in the evolution of be competitive and improve their customer service longer term. n
machine designs, upgrades for users and off-site remote services
such as maintenance monitoring and repair requests. Similarly, *Dave Wibberley, info@adroit.co.za, Tel 011 658 8100,
fleet monitoring provides a window to part failures, spares Mobile 083 601 7008, Web: www.adroit.co.za

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