Remote condition monitoring must not be overlooked in energy efficiency strategies
Author : Mike Burrows | Senior Advisor on Industry 4.0 | RS Monition
03 March 2020
While the advantages of remote condition monitoring are widely recognised as part of a predictive maintenance strategy, its use as a direct energy management tool has not yet been widely adopted in industry.
This article was originally featured in special supplement on Designing for energy efficiency, brought to you by EPDT & RS Components [read the digital issue].
Perceived hassle has been a prohibitive factor, with the benefits possibly deemed not significant enough to warrant the investment of both time and money, given many industry sectors have different drivers in terms of budget and benefits. Here, Mike Burrows, Senior Advisor on Industry 4.0 at RS Monition, the asset reliability & condition monitoring services arm of RS components, explains why it should not be overlooked when designing your energy efficiency strategy...
With the arrival of Industry 4.0, emerging technologies are enabling the required connectivity, providing ease and accessibility across machines/areas and sites. Couple this with a growing energy efficiency agenda, and the ability of the application to understand not only condition, but also performance across the business network, and the concept becomes increasingly attractive.
The relative cost of energy in production processes continues to grow on an annual basis, while conversely, use of energy management systems (EMS) is only typically deployed by those industries with high energy demands, such as paper, steel production, and chemical or petrochemical. However, digitisation of manufacturing will cause this to infiltrate other sectors and become more of a global trend (indicated by the emergence of companies providing remote services for energy optimisation). In a world where energy is a capital acquisition consideration when purchasing manufacturing equipment, the benefits of remote condition monitoring, coupled with the IIoT (industrial Internet of Things) and Industry 4.0 movement, can no longer be sidelined.
The energy impact of optimising machine tools
One reason why remote condition monitoring with an energy efficiency motivation has been overlooked is possibly because of the perceived low value/impact of benefits at an individual unit level. However, the availability of cloud solutions for data collection, storage and analysis – accessible anywhere in the world – has proved a game changer. For example, when applying the concept of creating a ‘power profile’ of machine tools across multiple axis drive motors, establishing the optimum ‘cutting’ program, collecting local power info and sending it to the cloud for machine learning, information can be used across each machine in the plant and AI (artificial intelligence) applied to close the loop. The programs can be fine-tuned to maximise energy efficiency and usage. The wider application is then to remotely monitor the individual machines performing the same task in the plant and other sites worldwide, and apply the same power profile to all.
Proof of concept
RS Monition was involved in such a project to prove this concept, with energy consumption monitoring and profiling being executed and applied using easy-to-implement condition-based maintenance (CbM) techniques. The aim was to use this as a mechanism to improve overall business effectiveness, with a triple perspective:
1. Optimising maintenance strategies: based on the prediction of potential failures, helping guide the planning of maintenance operations – allowing scheduling of maintenance operations in convenient periods and avoiding unexpected equipment failures
2. Operation: managing energy as a production resource and reducing its consumption
3. Product reliability: providing the machine tool builder with real data about the behaviour of the product and its critical components
The information gathered enabled identification of maintenance issues across the machine and individual components, as well as setting of an optimum program to reduce energy and establishment of best-fit settings against power. The concept is similar to a test page in a printer – which ensures that the machine setting (maintenance), program and materials are all in spec. This reduces rework, increases yield rate – and no unnecessary power is used.
By looking dynamically at the machine parts, analysing the impact of common variables, such as a change in materials or batch of materials being used in the manufacturing process, the system was linked to the cutting program and energy reading simultaneously across all drives every 100 milliseconds. This allowed the effects of program and process changes to be understood, and ML (machine learning) applied to achieve the optimum energy consumption. Getting this power profile right will have the most significant impact on energy reduction when applied across multiple machines all doing the same job, and within organisations with multiple plants – whether nationwide or global. Energy monitoring and power consumption analysis provides the ability to predict machine malfunctions, which can facilitate the introduction of predictive technologies in more complex production environments. This is not an exercise with intangible benefits, but one that should be a real consideration in any maintenance strategy that prioritises effective energy management.
The positive effect of changing mindsets
The above example is focused on an asset type, but the same principles and logic can be applied across all machines: the value is in the collective understanding and ensuring actions is taken from the information provided. What we must never forget is that condition monitoring only informs on the condition; it is action taken on the back of this information that will make the difference.
While on the quest for improvement, it’s also important to take time out to look at how behaviour within our plants can be influenced. Just as we often display OEE (overall equipment efficiency), a tactic we used while implementing energy saving strategies was to put in place visual power readings on machines. This simple and cost-effective measure raises awareness to machine operators of its power consumption, bringing the issue to the fore. Including this human element, alongside condition monitoring and IIoT technologies, provides a multi-pronged approach to an issue that cannot be tackled effectively by one singular tactic or effort.
IIoT technologies have brought countless benefits to the factory floor, and will continue to do so. The ease of connectivity of instrumentation, an open architecture providing a common language and cloud solutions are just a few of the elements facilitating accessible implementation of remote condition monitoring, delivering very real benefits. This is turning what was once science fiction into ‘science fact’ – bringing everyone in the industrial sphere that bit closer to the true factory of the future.
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