13 Elements of Intelligent Asset Management for the Mining Industry
by Drew Troyer, CRE, CEM
Principal Director
Accenture – Intelligent Asset Management (IAM)
Success in the mining industry comes down to three basic factors: 1) market demand for mined materials; 2) geological quality of the mine; and 3) performance of the physical assets employed for extracting and converting ore into a saleable product. The market is what the market is. Most miners serve commodity markets – they’re price-takers and have little individual impact on the price of goods sold, which generally tend to be inelastic. Likewise, geology is what it is. If the geology isn’t good, we’re not going to mine that site anyway. The performance of the firm’s physical asset for extracting and converting ore is management’s most controllable factor. Managing assets intelligently profoundly affects production, profitability, environmental performance, and safety. All the organisation’s dashboard goals depend upon asset performance.
I’m often asked, “what does Intelligent Asset Management look like?” How does one recognise it when he or she sees it? While there are plenty of details – and it varies some from industry to industry, I’ve boiled it down to the following 13-dimensional elements that I’ve described here in summary form (Figure 1).
THE 13 ELEMENTS IN SUMMARY
1. Strong leadership focus and business-aligned plant reliability mission, vision, and strategic plan
Your leaders, both at the corporate and plant levels, must keenly understand the impact reliability has on the bottom-line performance of the organisation, including the share price. The valuation of an equipment asset-dependent organisation is significantly affected by the effectiveness with which that equipment is managed. Your leadership must understand that reliability management is not just doing maintenance better. Without knowledgeable and truly engaged senior leaders who are willing to make plant reliability management a matter of corporate policy, it’s not likely that you’ll gain traction and achieve lasting improvement.
2. Effective inter-functional and interplant communications
Unfortunately, when things go wrong, the typical modus operandi in most plants is to begin the process of assigning blame. Operations blame maintenance, maintenance blames operations and the design engineering group, everybody blames suppliers, and so on. Rarely does this process yield productive results. Poor communication between co-dependent functional groups almost guarantees poor reliability performance. Moreover, organisations that have multiple plants often fail to take advantage of the knowledge and economy of scale afforded to them, either because of a culture of internal competition or the lack of effective interplant communication systems through which to share knowledge and experience.
3. Focus on design for reliability, operability, maintainability, safety, and sustainability (ROMSS)
Most organisations have attempted to improve reliability strictly from the maintenance department. It simply doesn’t work. Poor overall reliability is the result of poor basic “design for reliability,” given the required operating context; improper operation, which may be the result of poor “design for operability”; and ineffective maintenance, which may be the result of poor “design for maintainability”. Some studies suggest that half of all failures are directly attributable to poor design. Designing reliable equipment and plants requires risk assessment, clear knowledge of the operating context, involvement from operations and maintenance domain experts, and a leadership focus on minimising life-cycle costs.
4. Reliability-focused operations
Equipment that is started, stopped and/or operated incorrectly, or beyond its operating limits, will simply experience a higher failure rate. A reliability-focused operations team follows and enforces well-conceived standard operating procedures. They also understand that, in some instances, producing more can result in profit erosion. The mentality extends beyond plant operations to the sales and marketing department. An enlightened sales and marketing team understands that the profitability of sales contracts and the reputation of the firm depend upon the reliability of the machines or plant, especially when transactions carry penalties for late or non-delivery – in some cases, total-loss penalties. They factor projected reliability into their pro forma estimates of contract profitability. The reliability-focused operations organisation works closely with the maintenance team, particularly to provide inspection and operating health feedback regularly, and supplies design engineers, procurement specialists and strategic suppliers with the information they need to improve equipment operability.
5. Reliability-focused maintenance
While maintenance can’t improve the reliability of equipment, they can ensure that its inherent reliability, based on design and operating context, is maximised. A reliability-focused organisation doesn’t just employ modern techniques like Reliability-Centred Maintenance (RCM), condition-based maintenance (CBM) and precision maintenance techniques. A reliability-focused maintenance organisation works hard to optimise maintenance activities, with a focus on running time activities. It also works closely with operations to ensure that the equipment is available to produce as much product as required, meet quality goals and, most importantly, satisfy customer demands. And, a reliability-focused organisation works closely with design engineers, procurement specialists and strategic suppliers to improve design for reliability and maintainability, and to avoid purchasing the same problems repeatedly.
6. Effective talent management
The success or failure of your reliability management program will ultimately come down to the people who are involved. Effective plant reliability leaders recognize that talent management goes beyond just hiring people with the right skills for the job; performance is also a function of behaviours. Skills can be taught; behaviours can’t. It is quite difficult to significantly modify an individual’s behaviours beyond a temporary interim period. Effective plant reliability management requires that you identify the behavioural characteristics required to succeed in your organisation and the job, the skills and knowledge required for the job, a method for assessing both, and tools and techniques for managing and retaining your talent. In the tough talent market projected for the future, talent management may differentiate the winners from the losers.
7. Strategic customer and supplier relationships
Suppliers and customers alike are critical to the success of your reliability program. A major component of the Toyota Production System (commonly referred to as lean manufacturing) is negotiating production and delivery time with the customer, both internal and external, for load levelling. At times, delivery deadlines aren’t deadlines at all; they are just dates that are selected. Understanding which delivery deadlines are real and which ones are arbitrary can help you openly discuss matters with your customers. This helps you create a pull-based production system while avoiding the added stress on the equipment and organisation to meet arbitrary deadlines. A similar strategic relationship must exist with your suppliers. A vendor is a machine that dispenses a soft drink or snack in exchange for money. You need strategic supplier partners, both for process and MRO materials. Strategic partners bring important knowledge and experience to the table, which enables you to plan more effectively; improve design, operations, and maintenance; and more effectively assess problems and shortcomings.
8. Reliability data collection and analysis systems
Reliability management and improvement require data. Surprisingly few organisations collect, analyse, and manage reliability data effectively. From a technical perspective, reliability starts with a failure modes and effects analysis (FMEA), the reliability blueprint of an operational service or machine. Often, the FMEA is completed by drawing on limited data experience, and that is the end of the process. The FMEA worksheets serve as a reliability growth management tool. Each time you learn something new, you modify the FMEA and its associated risk priority number (RPN), a 1 to 1,000 rating of the risks associated with a failure based on severity, likelihood, and detectability. This means the organisation’s plant must be committed to collecting operational and maintenance-related data – both when things are going well and when things go wrong. Mathematical reliability engineering methods and associated tools (such as root cause analysis) enable you to implement information-based improvement initiatives. Performance monitoring and detailed failure data collection techniques are an absolute must.
9. Procedure, document, and knowledge management support systems
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In applications where failure risk is potentially deadly, such as the commercial aviation industry, managers long ago stopped relying on the “skill of the operator” or the “skill of the maintenance craft.” Standard operating and maintenance procedures combined with checklists define expectations. Procedures and checklists are necessary to ensure consistency of practice among different people and over time. And, when staff changes do occur, procedures are required to assure continuity. Too many plants have too much of their intellectual property residing in the heads of staff members that could resign, retire, or take ill at any time. Procedures also clearly define skill requirements for a particular job or activity. The modern, reliability-focused organisation employs clearly defined operating, design and maintenance procedures, enforces them, and incorporates easy-to-use systems for executing work and managing change.
10. Targeted leading and lagging metrics
Leading metrics reveal performance on causal factors that, when effectively managed, yields desirable performance on lagging indicators – the effect. For example, it’s common for Japanese plants to track the number of small group meetings they have related to Total Productive Maintenance (TPM). The premise is that more small group meetings result in better communication between functional groups (the cause), which results in fewer mistakes, better plant performance, and improved efficiency and effectiveness in responding to problems and opportunities (the effect). To be effective, your metrics, both leading and lagging, must accurately reflect reliability goals that align with the organisation’s mission. The management team must understand that cause and effect probably won’t be time-synchronous, hence the term “lagging.” Also, left unchecked, metrics can take control of your organisation. Don’t let the organisation focus so much on the metric that it loses sight of the mission. To paraphrase W. Edwards Deming, don’t allow metrics to replace leadership, judgment, and common sense.
11. Vision-centric team reward system
What gets rewarded gets done. Despite this obvious fact, we’ve got a long history of rewarding failure in industrial manufacturing plants, both extrinsically and intrinsically. For example, when a machine fails over the weekend without warning and technicians are called in to address the event, they are extrinsically rewarded with overtime pay. For many, failure-induced overtime pay is so common that the technicians have adjusted their lifestyles to reflect it. Moreover, when the plant manager or maintenance manager returns to the plant, he or she rightly seeks out the technicians responsible for restoring operations and intrinsically rewards them with thanks and praise for their efforts. In both cases, the rewards are appropriate; but in both cases, they create an incentive for unreliability. Reliability-focused organisations reward reliability, not failure. The reward structure must be modified to create an incentive for the desired behaviour.
12. Sustainable asset management
Physical asset utilization in the manufacturing, process, mining, and other heavy industries is inherently energy and resource-consumption intensive. However, the way we design the products we make, and the assets required for production, can dramatically impact the organisation’s environmental and social impacts. Sustainable asset management is a subset of the general discipline of sustainable manufacturing. The focus of sustainable asset management varies across industries. However, in all instances, success centres heavily around energy consumption and energy management. The US Department of Energy (DOE) estimates that most industrial facilities can reduce their energy consumption by as much as 20% by implementing known best practices that employ existing technologies. They estimate greater opportunities with investment in technology. Managing combustion efficiency, transfer of electrical and mechanical energy across intended pathways, and minimizing leaks and fugitive emissions enable asset managers in the plant to improve energy efficiency. Designing equipment and plants for energy efficiency sets the stage for success.
13. Reliability culture management
Arguably, the most difficult aspect of plant reliability management is creating a reliability-focused culture. People and organisations like to hang on to past practices, resisting change. “We’ve always done it this way” is commonly heard around the plant. The desire to anchor to what has always been done is a phenomenon referred to as “psychological inertia.” Reliability-focused organisations continuously question current practices and look for ways to improve. This pattern of behaviour takes time to establish and much work to perpetuate. It’s imperative to create a plan for achieving behavioural change, starting with lead users and early adopters, and gradually making it to those people who are slower to adopt or who actively oppose the change. There is a point at which a sufficient percentage of the organisation will come around. That is when you’ll achieve critical mass. But getting to that point requires leadership, patience, and tenacity. Once you’re there, you must keep the pressure on until the new practice becomes a “new business as usual” to replace the old one, or the organisation will gradually slip back into its old comfort zone.
YOUR NEXT STEPS
Few people dispute the importance of asset performance in mining and other asset-intensive industries. Asset performance drives value and substantively contributes to achieving sustainability, safety, and other dashboard goals. However, achieving excellence in Intelligent Asset Management isn’t easy and it doesn’t happen by accident. My advice for you to get your journey started, or reinvigorated back on track if initiatives have been derailed in the past, is to create and execute an Intelligent Asset Management plan in the following six phases.
I. Element Prioritisation – Each of the 13 elements of Intelligent Asset Management described here is to a greater or lesser extent applicable to all organisations. You must agree on a weighting of each element for your organisation. This can be accomplished by conducting a cross-functional weighting process using a Delphi analysis or some other process that minimises individual and group bias.
II. Assess Your Strengths and Weaknesses – Once you’ve prioritised each element, you must evaluate your strengths and weaknesses. This needn’t be too detailed an analysis at this phase in the process. You’re simply trying to determine strategic vectors so you can assign the right amount of resources and priority in the right directions of Intelligent Asset Management.
III. Assess Your Opportunities and Threats – Improving the performance of your equipment assets requires an investment of time and resources. We must ensure that it delivers value in the form of increased production throughput, decreased maintenance, operational, and/or energy costs, improved safety of operations, and generally reduced life cycle costs and environmental impacts of your equipment assets.
IV. Deep Dive Your Priority Vectors – As discussed in item I above, the preliminary strategic analysis of strengths and weaknesses typically reveals that the 13 elements aren’t equal in importance. For the priority items, it’s often necessary to deep-dive to gain a thorough enough understanding to develop a tactical improvement execution plan. In some cases, this can take some time and effort. But it’s better to measure twice and cut once to minimise mistakes.
V. Create a Long-Term Execution Plan – We all want to get short-term wins on the board – and we often do have wins available to us. However, I’ve found that replacing an existing and undesirable “business as usual” with a more effective “new business as usual” requires a long-term plan of at least five years or more. A new business as usual won’t occur spontaneously. It must be engineered to include a) optimized intelligent asset management business processes; b) technology integration that supports business processes; c) education, training, and skills management; and d) documentation of practices for continuity (Figure 2). Above all, success requires relentless leadership. You’ll want to ensure that you follow a well-defined and properly sequenced plan to ensure success.
VI. Get to Work and Track Your Progress - You’ll want to track your benefits as you go. If your scope, timeline, and critical path are well-defined and you effectively track your progress, your Intelligent Asset Management transformation should be cash flow positive relatively quickly.
FINAL WORDS
Mining companies, as well as companies in other physical equipment asset-dependent organisations, depend upon the performance of those assets to drive value, reduce environmental impacts, and minimise safety risks to employees and community stakeholders. Of the three success drivers for mining companies – market conditions, geological quality, and asset performance, managers have the greatest ability to impact asset performance. Here, I’ve summarised Intelligent Asset Management into 13-dimensional factors. An analysis of your strengths and weaknesses along these 13 dimensions combined with an analysis of the opportunities to improve productivity, profitability, safety and environmental performance and the threats to effective implementation yields a highly focused Intelligent Asset Management strategy and plan.
About the Author
Drew D. Troyer, Principal Director with Accenture Industry X. A global thought leader in Intelligent Asset Management (IAM), Drew has more than 30 years of field experience and has authored more than 350 publications on various asset management and sustainability topics. He’s a trusted advisor to a global blue-chip client base. Certified Reliability Engineer (CRE), Certified Energy Manager (CEM), and a master’s degree in environmental sustainability from Harvard University are among Drew’s many qualifications.