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Poorly planned maintenance strategies can reduce a typical plant’s overall productivity by as much as 20%1, while recent studies confirm that unplanned downtime is costing industrial manufacturers an estimated $50 billion every year.1

This puts the focus on efficient and timely maintenance to support a productive manufacturing operation. By keeping equipment in good condition – and downtime to a minimum – organisations can realise greater value from their assets and investments, for less cost.

Traditionally, manufacturing maintenance has been performed in one of two ways. Planned maintenance is where servicing tasks and upgrades are scheduled at regular intervals in known time periods, such as daily or weekly.

Here, downtime occurs, but because it’s factored in advance, disruption can be limited and factory teams can use a contingency. Although of course, some production time is inevitably and unavoidably lost regular servicing can reduce the impact of discovering an unexpected problem and the resulting impact of this lost time is lessened.

In contrast, unplanned maintenance happens on-demand, according to equipment performance. In some circles ‘sweating of the asset’ – working it at full capacity and maximising ROI - relies upon effective maintenance to provide uptime.

When it eventually breaks down, it might have been ultimately less disruptive in terms of downtime, but its behaviour is also less predictable as little to no routine maintenance is conducted. So, there is the risk of a sudden and significant monetary outlay and productivity loss.

Put simply, while a ‘run-to-failure’ approach might be OK for certain machines, unplanned downtime is almost always more expensive to correct. As such, planned maintenance has typically been the preference.

However, as plant machines get more complex in construction, with more technology inside, so there are more sensors and parts to maintain – and ironically more potential failures within the network path. Routine maintenance is consequently becoming more complex and potentially expensive, meaning older, simpler machines are actually more reliable from an OPEX perspective.

As modern equipment is designed for modular component swaps, the speed of service may be faster and spares may be more expensive.

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predictive maintenance

Article Gain greater value from your factory assets, with predictive maintenance

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Therefore, planned maintenance is becoming increasingly important to extend life, reduce downtime and help manage stock and inventory. It also has significant benefits for safety in the modern manufacturing environment.

Properly planned maintenance allows the appropriate suitable skills to be allocated for every critical maintenance job - either by pre-booking specialist engineers or equipment.

This is a much better solution than relying on the nearest available technician to step in as and when equipment malfunctions: that person may not be best qualified and ultimately, their safety may be put at risk.

Of course, ideally by ensuring machinery does not break in the first place due to ongoing and appropriate maintenance, your plant will avoid putting anyone in its workforce at risk, altogether. Possible risk scenarios include someone operating an overhead crane that has not been inspected properly, or people getting stuck in a lift which has not been serviced punctually.

"One concern that organisations have is how they’ll manage the large volumes of sensor data from a widely distributed base of connected devices. It challenges the conventional data storage and management capabilities of most businesses. The volume and velocity of sensor data flowing into organisations make drawing insights particularly challenging. Many organisations lack stream-processing capabilities, which are essential for the collection, integration, analysis and visualization of data in real time."

Eric Veldkamp, Partner at HSO’s Software Division Dynamics Software

PREDICTIVE ANALYTICS AND THE SMART FACTORY

Analytics is nothing new for manufacturing. Manual guess or intuition-based forecasting is well-established and has been used to predict maintenance requirements for some time. However, its accuracy was often questionable given the discrepancy between data quality and methodologies involved.

The Internet of Things (IoT) is transforming this process. With innovations such as multiple sensors embedded in machines, and advanced algorithms sweeping through data sets to identify key trends and issues, predictive analytics is creating exciting new possibilities using accurate, timely information.

Digitisation enables manufacturing companies to transform their traditional facility into a fully-functioning smart factory which makes them more globally competitive, operationally efficient, safer to operate and customer-centric.

Predictive maintenance is a central component of this. Using historical performance as a guide, advanced software forecasts how monitored equipment and the entire production line will behave, and when and where intervention is likely to be necessary.

As such, operators can be empowered to identify and resolve issues before they significantly impact the business or require a need for specialist engineers, and save considerable expense in the process as well as extending overall machine lifetime. Indeed, the industrial IoT market is currently valued at $11 trillion and predictive maintenance can help companies save $630 billion over the next 15 years3.

Manufacturers are set to spend

some $74.8 billion a year on smart

factory technology by 20222, while

McKinsey & Company estimates

that by 2025 the total economic

impact of smart factories could

reach $3.7 trillion per year2.

“Many companies have made the shift from corrective to preventive maintenance in recent years. Especially in industries that require high capital investments in manufacturing equipment, the need to avoid breakdowns or unscheduled maintenance during production hours was imperative. Predictive maintenance is the next step for these industries.”

Wim Pluimers, Product Director, Maintenance Management at HSO’s Software Division Dynamics Software

HOW PREDICTION BOOSTS PRODUCTIVITY

Predictive maintenance offers four key benefits: improved product quality, increased productivity, reduced downtime and costs, and faster, more informed decision-making. By experimenting with different maintenance approaches and strategies, your individual business can assess their effect on overall performance, identify possible weaknesses in machines and infrastructure, and determine the most effective scenario for your needs.

For example, you can see which areas of your line are likely to fail first, or need replacing soonest. So, your teams can accurately manage inventories and store or order relevant parts in advance of when they are required. In turn, they can also create reliable cost benefit analyses and manage risk.

Once established, a predictive solution gives operations the freedom and confidence to plan repair and maintenance activities to ensure they deliver maximum value and effectiveness – with minimal disruption to your existing manufacturing processes. This also reduces administrative work and eases the burden on human resources.

In between these interventions, costs and time can be further saved by identifying opportunities for greater

efficiency, based on predictive maintenance insights. Machines that are running slightly hot, or not quite optimally, can be fine-tuned to improve performance in real-time, without any interruption to normal processes. Managers are fully informed about their overall factory and equipment, with visibility that helps maintain competitive advantage.

“Everything Azure delivers is already integrated well with our existing systems. With the cloud-based technology Microsoft provides, we have all the tools from one supplier — from Azure to Dynamics 365. We have worked with a company that rents out generators to predict the best time for maintenance By developing a solution based on Azure IoT Suite, Dynamics could help them shift to predictive maintenance based on actual usage rather than scheduled maintenance that was too early or too late.”

Eric Veldkamp, Partner at HSO’s Software Division Dynamics Software

A TREND TOWARDS TWINNING

Digital twinning – the meeting of digital and physical technologies – is big news. Digital twinning itself is a driving force behind predictive maintenance. Tasks can be virtualised using a digital representation of what is going on and what needs to happen inside a particular machine. These digital renderings can be viewed from anywhere, on mobile devices or computers, so engineers can intervene swiftly and cost-efficiently.

Drawing on machine intelligence – which is constantly evolving and learning – smart factories can use these automated technologies to make accurate decisions according to real-time events.

As more data is collected over time and decisions play out, technicians are able to create virtual prototypes to test theories for improving productivity and operations.

Article Gain greater value from your factory assets, with predictive maintenance

By 2023, analysts predict that

85% of IoT-enabled platforms

will have digital twinning

functionality4.

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Article Gain greater value from your factory assets, with predictive maintenance

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Everything can be managed and generated remotely, which shortens timelines and keeps costs down. Then, once implemented, these prototypes can be refined and developed further based on data insights and performance metrics, gleaned from a raft of physical sensors. Virtual replicas can make a demonstrable difference across multiple areas of manufacturing, including product design, asset management, infrastructure, and production.

HOW HSO HELPS MERBA UNDERSTAND ITS MAINTENANCE NEEDS

Microsoft’s manufacturing division is already working with a number of forward-thinking organisations to deliver effective predictive maintenance solutions based on the Microsoft Azure IoT Suite and Azure Machine Learning. As a valued Microsoft partner, HSO is contributing to this educational and innovative transition process.

One such customer HSO has worked with is Merba, a high volume, globally active industrial cookie manufacturer. Established in 1932, Merba has over 180 employees, has introduced multiple products to worldwide markets, and exports its cookies to around 70 countries around the world.

Merba needed a strong ERP product, capable of integrating all its corporate information to provide actionable, accurate information about operational performance. Its existing application used a siloed application with a database structure which was not SQL based. Extracting valuable information from it was a big challenge, and it was difficult to maintain on that basis.

HSO worked with Merba to deploy Microsoft Dynamics. As part of this solution, HSO’s software division Dynamics Software (DYS) deployed their Maintenance Management module for Dynamics 365. Merba

now enjoys real-time, highly accurate insight into its production performance, possible operational issues and overall maintenance needs. Maintenance workers themselves can respond to breakdowns quickly with potent solutions and informative reporting, including hours logged, parts availability and cost of repair.

MAKE THE MOVE TO PREDICTIVE MAINTENANCE

Predictive maintenance is no longer in its infancy. Specialised algorithms are available and blended into software solutions which provide information to help companies improve operational efficiencies and secure deliveries. An effective predictive maintenance strategy is an essential part of your digital transformation journey for production, customer satisfaction and machine safety.

As predictive maintenance increasingly moves away from human-driven teams towards machine learning systems and widens its influence across all areas of infrastructure, we’re likely to experience noticeable service improvements both on the factory floor and in customer experience. Without doubt, the era of machine learning is here. It’s vital for your organisation to embrace it, and make the necessary technology investment to reap the rewards.

MICROSOFT DYNAMICS MAINTENANCE

As a dedicated, ‘all-in-one’ solution, Dynamics Maintenance gives your organisation access to real-time information which will enable you to optimise your plant’s preventive periodic maintenance and internal maintenance requests, as well as repairs. Get immediate data insight relating to your equipment, resources and logistics, when you need it most.

Find out more here.

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SOURCES:

1 Deloitte2 Prismtech 3 McKinsey4 JJ's Manufacturing

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WHO IS HSO?

HSO is a Microsoft Gold Partner with over 25 years of experience in implementing ERP solutions. We’ve been named a member of the Inner Circle for MicrosoftDynamics partners for eleven consecutive years.

Learn more at www.hso.com

ABOUT MICROSOFT DYNAMICS 365

Microsoft Dynamics 365 makes it easy to operate across multiple locations and countries by standardising processes, providing visibility across the organisation,and helping to simplify compliance.

HSO has the specialist expertise to deliver industry-focused Microsoft Dynamics 365 implementations for customers in retail, distribution, and manufacturing.