Addressing maintenance challenges using EAM
Enterprise Asset Management (EAM) addresses the entire lifecycle management of physical assets of an organization in order to maximize value. It is a discipline covering areas such as the design, construction, commissioning, operations, maintenance and decommissioning or replacement of a plant, equipment, facility or some other high-value asset.
A high-value asset is one that has a significant operational and financial impact on a company’s main line of business and profitability. It is “Enterprise”, because it spans across departmental, locations, facilities, business units, and geographies. The ultimate goals of managing assets in this way include:
- Improving utilization and performance
- Reducing capital costs
- Reducing operating costs
- Extending an asset’s life, and subsequently
- Improving ROA (return on assets)
Enterprise asset management (EAM) is a powerful solution that can help organizations strike the right balance between operations and maintenance by keeping critical assets and resources operating at maximum efficiency; connecting plants, sites and teams; and providing guidance and support to help maintenance teams do their jobs more safely, correctly and faster.
Common organizational challenges which can be addressed through EAM
A primary challenge many asset management teams face is gaining executive support for anything they do around maintenance or asset management. While the process is getting better, in many cases the same challenge has existed for a least a decade – asset management operates like a cost center, one which is perceived as a necessary evil to meet regulatory and safety demands. It’s not regarded as a strategic part of the business. As a result, operations and maintenance (O&M) leaders struggle to get respect from the rest of the organization. They may gain respect when they fix the asset – once it’s broken, but, when they have to do preventive maintenance or if something does go down, they tend to be the first ones to be blamed and the last ones to be on the receiving end of funding for anything other than asset replacement.
2. Losing organizational knowledge through a retiring workforce
A second challenge many of enterprise organizations face is addressing the reality of a retiring workforce. For example, for many asset-intensive organizations, 50% to 75% of their maintenance workforce will be retiring within the next three years. These organizations are grappling with how to replace the knowledge which is being used now on the plant floor – vital experience which is keeping essential assets up and running, reducing down time, keeping the production lines running and equipment available.
3. Balancing day to day work prioritization with strategic transformation
A third challenge area revolves around the prioritization of work. How to get an increasing amount of work done, with a shrinking or flat budget; how to get tools to the right place at the right time; how to schedule work in order to optimize a better crew schedule. Fundamentally, asset management teams have two jobs – one which involves preparing the assets; and a second job to implement a practical asset management solution. It’s very hard for asset management teams to keep their heads in the present, while planning for the future – without losing track of the day to day requirements of the business.
4. Increasing asset sophistication and complexity
A fourth area which keeps people up at night is the sheer complexity of assets. As organizations become more instrumented, assets are becoming more complex in terms of what is running their operations. When you think of how the plant floor is evolving towards automation – the type of equipment being used – robots, sensors, and electronics – these things are all over the plant floor. They are more complex, and maintaining those assets is becoming more challenging. In the current environment, equipment is more reliable, but when it does fail, or require servicing, the difference between a physical production asset and an IT asset suddenly start to blur. On the outside of the asset there are the mechanical pieces, but inside the asset, there are a lot of IT hardware and software components to manage as well.
5. Managing the long arm of regulation
Another issue that organizations face today relates to government regulation both from OSHA, the FDA and EPA. Regulatory bodies impact other areas of business – not just highly regulated industries. Some industries – pharmaceutical, utilities, especially around nuclear – are highly regulated industries where OSHA has always played a part. However, as pressure from the FDA and the EPA are starting to spill over from pharmaceutical into the food area, especially around food safety and sanitation, the need to comply with regulatory bodies has emerged as an issue in general manufacturing and food manufacturing as a whole as well.
What’s driving change in asset-management approaches in organizations?
When you look at how manufacturing is changing and shifting, and examine how assets are being replaced on the line – becoming heavily sensor-ized and instrumented, with advanced robotic capabilities – the whole industry is becoming more technologically complex. When you take this issue and add it to a retiring workforce that has been using systems which are not digitized, or centralized into an accessible repository, organizations are looking at a major transformation speed bump.
Here are three core drivers to implementing change in an asset management strategy or the system used for EAM.
- Regulatory or risk issues. For example, something bad happens in the plant and it needs to be fixed because it’s been noticed. It could be a unplanned downtime that received management attention; or, an EPA or OSHA fine. These are the types of circumstances that drive an organization to make a change.
- Executive / Management changes. A new person comes in from another organization and implements changes, wants to do things differently because they had success at a prior organization.
- Data. The third driver, and this is really starting to appear more frequently, is the need to make use of the data coming from equipment and machines. As more instrumentation and sophistication appears on plant floors and across manufacturing and other asset-intensive organizations, the need to capture and turn the data flowing from equipment into intelligence will drive change.
A fourth driver is the information technology shift that’s taken place. Up until now, the shift has been platform-oriented – something no longer runs on Windows 8, or, the organization needs to upgrade or MYSQL server database, or the Oracle database is not compatible with what is supported on a global scale, or, so the organization needs to upgrade or do something different.
The convergence of EAM, IoT and machine instrumentation
Some companies still regard physical asset management as just a more business-focused term for maintenance management. In fact, the term “Computerized Maintenance Management System” or CMMS was commonly used to describe this market space. However, a holistic view that realizes the organization-wide impact and interdependencies with operations, design, asset performance, personnel productivity and lifecycle costs, extends beyond this limiting term. This expansion, or shift in focus, exemplifies the progression from maintenance management or CMMS, to Enterprise Asset Management (EAM).
The application of IoT capabilities becomes significant once people understand how to harness the information that’s coming off of their machines. This is where the preventive, predictive and prescriptive nature of maintenance can start to gain traction as these machines begin telling workers when they need to be maintained or when they should be PM’ed or when they’re about to break so that you can limit the downtime on operation.
However, although the use of preventive, predictive and prescriptive strategies can help asset-intensive organizations immensely, their mindset is not in the mode of investment – they may not yet see the value of these approaches. Sensors on machines, PLCs, and production lines have always been around – especially in the larger enterprise – automotive and aviation manufacturing, for example.
But what we are finding is that even though there are links into those technologies, organizations are only just starting to turn their priorities to using IoT as a means to capture information and knowledge digitally.
Taking advantage of asset instrumentation and sophistication
Maintenance organizations are fully engaged in the IoT wave, with leading analyst firms and plant publications indicating that they are using or planning to use IoT technology and solutions to improve their operational efficiency.
The difficulty is finding the time, bandwidth and funding to actually implement changes to take advantage of the sensors – to look beyond equipment as the only asset – towards seeing the data as an asset as well. If organizations are struggling to get their hands around basic maintenance strategies, it’s going to be difficult to position advanced strategies where a machine is telling them what to do.
The sophistication of equipment presents challenges in different fronts for asset management – which may involve different departments, suppliers, skills, and of course time. In addition to the physical attributes of the asset, there is also the data – the volumes of information flowing from each of these machines.
Finding ways to ensure each of these advanced machines and the data coming from these machines is meaningful is an area asset management teams are exploring. Through the machines, they have always collected a lot of information. Historically, organizations haven’t done much with that data – it’s been collected, but it is not being used as intelligence.
Getting beyond the hype
In some instances, market confusion is a factor preventing or impeding progressive change. Within many organizations, there is reluctance to take the step forward because people feel their workers may be replaced by these new intelligent machines.
IoT can help to address this fear – to overcome what Gartner refers to as the “hype cycle,” While many pundits and organizations are out there saying ‘this is what IoT can do,’ there are still no standards in place which enable an organization to instantly implement a solution – you can’t just buy one off the shelf.
If you look at the overall maturity curve in the US, outside of highly regulated industries, you’ll find that they’re very immature on the EAM side. While some organizations are doing PMs, the majority of their work is reactive or corrective maintenance, as opposed to preventive or predictable or prescriptive. For instance, what you’ll find in food manufacturing in particular, lags even further than general manufacturing from both line technology to maintenance technology.
On the consumer side, IoT does some fantastic things for business – for marketers, consumer information and supply chain management. The investment in these areas are being made faster and at a speedier pace than what we are seeing on the asset management side. Assets are not customer facing. IoT has taken off in areas that enable organizations to know their customer better – because they can sell more efficiently. This has a direct impact on revenue – which is where early investments with IoT have been made.
Changing attitudes – maintenance is not just a necessary evil
When clients talk about what is driving their maintenance strategy and how they approach operations, they say getting the product out the door – regardless of the cost. In good times or bad times, the costs are basically whatever it takes to get a product out the door.
If you have dedicated people focused how can to make the process of getting things out the door more efficient – with a goal to drive 10% out of that cost or 20% out of that cost, then there’s a quantifiable benefit associated with the process – which includes reducing the cost of the equipment required to produce the product – whether it’s a newspaper, a bottle of beer, electricity, water, or a car door.
Organizations are achieving huge gains in operating efficiency by implementing an enterprise asset management strategy.
IBM’s predictive and prescriptive maintenance offerings differentiate themselves with a breadth and depth of analytic capabilities. They include predictive models that can be tailored for specific use-cases, industry-models that accelerate implementation, and cognitive models that employ machine learning to correlate factors that deleteriously affect asset health, predict time failure and recommend appropriate changes to maintenance schedules and procedures.