Planning Plant Mods: Laying the
Groundwork for Success
Often completed late and over budget, plant modification projects can benefit from careful pre-project preparation and team selection.
By Russell A. Carter, Contributing Editor
There’s also another common trait that links these types of projects. According to studies, they consistently run behind schedule and cost more than anticipated. A 2017 McKinsey Co. report estimated that more than four out of five projects come in late, and over budget by an average of 43%. Five years ago, an EY survey provided similar results — projects were exceeding original estimates by 62%, and 50% of them ran behind schedule. Obviously, there are myriad underlying causes for project delays, cost overruns or other unfortunate outcomes. Project management experts suspect much of the diffi- culty encountered in reaching an intended solution stems from an incomplete understanding of the need for a plant modification and the requirements for keeping the project on track.
Not all projects fall victim to these problems. In fact, it’s fairly easy to find examples that bypass typical project snags and proceed to startup quickly and smoothly. Here are few instances: MATSA, a Spanish mining company based in the north of the Iberian Pyrite Belt, turned to Weir Minerals for a plan on how to increase its grinding circuit capacity from 275 metric tons per hour (mt/h) to 307 mt/h while reducing the quantity of ultrafine particles in the final overflow of the plant’s second hydrocyclone cluster. The miner had collaborated with Weir Minerals in the past to optimize the plant’s primary and secondary grinding circuits. “We have been working with MATSA for 12 years and our service team has built a solid partnership with them. We opened a service site close to MATSA and employed a full-time service engineer on site to provide adequate support,” explained Seda Kahraman, regional process engineer manager for Weir Minerals.
Weir Minerals took a holistic approach to the problem by first creating a simulation of the entire primary and secondary grinding circuit. This enabled them to visualize how the process should be running, and the most appropriate way to deliver the needed performance. Following the simulation, the best operating conditions were calculated to support the required capacity increase and elimination of slimes. This included the ball mills, mill liners and hydrocyclones. Using 3D laser scanner technology, Weir Minerals developed a layout for the equipment, including modification and steel structures.
To deliver the solution MATSA required, Weir Minerals replaced the primary hydrocyclone cluster, as well as the spare parts on the secondary hydrocyclone cluster; redesigned the steel structure and walkways; installed new hydrocyclone feed pumps and piping configurations. It installed and commissioned the entire project. According to Weir Minerals, modifications of the steelwork and piping along with assembly of a new three-way Cavex 650CVX hydrocyclone cluster were completed in less than four days without production interruptions. Upon analyzing samples from various points in the grinding circuit, it was confirmed that the feed capacity had successfully increased to 300 mt/h to 307 mt/h.
“In addition to the increase in grinding capacity, we also improved circulating load in the primary ball mill and restored the feed pressure to the hydrocyclones to 85 kPa. We are thrilled that MATSA achieved payback in just three days due to the increase in production and achieved additional revenue of €2,751 per hour,” said Kahraman.
MATSA Plant Technical Director Antonio Gamiz summarized: “To maximize our plant productivity, we needed a Cavex hydrocyclone cluster that was specifically designed to our application. This was achieved without an extension of the plant area and with minimal capital expenditure.” Another recent modification project that, according to reports, was completed on schedule and under budget is the pyrite leach project (PLP) at Newmont Goldcorp’s Penasquito gold/silver mine in Mexico. In late 2018, when first production from the circuit was announced — and prior to the Newmont- Goldcorp merger — Goldcorp CEO David Garofolo pointed out that the project had reached the commissioning stage two quarters ahead of schedule, and the overall project completed 9% under budget.
At the time of the announcement, the project was expected to recover approximately 35% of the gold and 42% of the silver reporting to the tailings and was expected to add production of more than 1 million ounces (oz) of gold and 45 million oz of silver over the current life of the mine. The PLP plant processes the existing plant tails, feeding a sequential flotation and leach circuit with precious metals recovered through a Merrill Crowe process, producing doré as the final product. Tails from the new plant report to the existing tailings storage facility. The company said that as the plant was ramped up to achieve design recovery, it would undergo optimization of the circuit chemistry and regrind performance.
Prior to the startup of the pyrite leach circuit, the company had just completed installation of a Carbon Pre-flotation project (CPP), which it said was integral to the performance of the PLP and existing plant. The CPP was commissioned in October 2018 within schedule and by the time the pyrite circuit was implemented, the CPP had treated 6 million mt of high-carbon ore and was exceeding initial performance expectations.
Handling the Unexpected
There probably isn’t a single definitive answer as to why some projects proceed smoothly to completion and others seem to encounter endless problems along the way. It’s likely that most projects encounter at least a few unexpected hitches sometime during the process. The key, according to experts, is to have a project plan and staff in place that can handle unexpected problems or change orders without complete disruption of the overall scheme. Turning back to the McKinsey report, the authors drew up a list of six ways to keep new projects on track — and to intervene quickly and effectively when they show signs of “heading south.”
Here they are, summarized to conserve space: Build a proven team – When a project is in trouble, many organizations attempt to turn it around by parachuting in individual experts rather than a cohesive turnaround team. This approach seldom works effectively. These may be accomplished leaders, but too often, the sum of their experience adds up to less than their individual skills. At best, they struggle to integrate their thinking and identify priorities. At worst, they develop ineffectual plans by consensus after prolonged debate. An effective turnaround team must bring collective, integrated intelligence to performance problems and focus on identifying specific ways to solve them. As early as possible once it becomes clear a project is in distress, the owners should create such a team with people, from inside and outside the company, who are willing to work together and have turnaround experience and complementary skills.
Create a comprehensive view of the project – Distressed projects, by definition, need improvement in many ways. The issues, ranging from contractual disputes and technical problems to unrealistic targets and poor morale, are often deeply rooted and interconnected. Diagnosing what’s gone wrong requires digging into the root causes of poor performance. Of course, there will be specific problems, but it’s important to recognize that these are often — even usually — the product of broader issues. One way to develop a broad picture of the changes required is to create a diagnostic framework that diagrams the organization of key construction activities, along with their supporting functions (contracting and quality, for example) and the way they interact, so people can visualize how related issues are connected. Since no turnaround team can do everything at once, it’s important to identify the fixes that bring the biggest benefit in the shortest possible time.
Address productivity issues – Raising productivity is one of the best opportunities to improve a project’s outcome and bring costs under control. Productivity tends to deteriorate when problems accumulate, and work becomes more complex. As the end of a project nears, tasks are congested, and multiple trades try to work in the same spaces. To overcome these issues, project leaders must address factors such as work patterns, work flows, and availability and skills of personnel. Many complex projects are located in remote places, so every available work hour must be used well. Successful workflow planning relies on predictable schedules — both daily and weekly — and on cooperation. Collaborative problem-solving among trades and between contractors and subcontractors is essential to reduce variability.
Establish an information infrastructure – To manage a major project effectively, managers must know what’s going on across all phases and scopes of work, so complete, constantly updated information should flow to everyone who needs it. A comprehensive dashboard that aggregates and analyzes data can give management teams the intelligence they need when they need it. Think of such a dashboard as a control tower that sends out crucial data to both management and on-site teams. It can be located in a space near the work site, with up-to-date progress metrics, graphs and drawings for the construction teams to consult. Ready access to information about a project’s progress and risks actually helps the various actors to improve their decision-making — an essential step to improving outcomes. A solid information infrastructure can help managers make better day-to-day decisions, adapt to changes and difficulties, and maximize the use of field hours across all phases of work.
Actively manage the transition from construction to operations – Mining companies often attach too much importance to meeting construction milestones and underestimate the effort required to commission and start up a plant. Those who build a project emphasize completing the work and moving on to the next assignment. Those who will actually operate the facility don’t know the details of construction and, perhaps, how the project was designed or decisions were made along the way. It’s a case of handing over the keys without an instruction manual. At this point, many promising projects take a turn toward disaster. Planning for successful transitions has to begin at the start of a project and remain part of the workflow throughout its duration so that the operations team becomes familiar with facilities as they are built. Close interaction between construction and commissioning leaders is required to get systems and subsystems safely across the completion line.
Define success – Projects don’t stop when they are in trouble. They are often well into the execution phase when problems arise. So, when a project owner must intervene to turn a project around, it should recognize that contractors and managers, working against long-established execution plans, are probably already invested in past decisions and practices. That gives large-scale projects a degree of both inertia (“we don’t want to change”) and momentum (“we’re busy”), which can slow progress. The improvement plan must include a significant change-management program, and the intervention leaders should be skilled at driving cultural shifts in project teams.
The industry’s expanding implementation of IoT, Big Data and AI systems may give companies a false sense of awareness or familiarity when it comes to applying information to project planning. The McKinsey report authors noted that “…one of the biggest challenges in today’s mining sites is that despite technological advances, critical data (such as cost and schedule metrics) reside in separate systems that don’t communicate.” Anthony Tarsilli, director of Minset, an Australia-based business-improvement consultancy, pointed out that possession of gigabytes of data isn’t a guarantee of better results in everyday operations or for projects aimed at achieving higher performance.
In a blog post titled, Data Isn’t a Default Ticket to Improvement, Tarsilli presented five core considerations that Minset has identified across numerous projects to help teams effectively use increased data availability for improvement:
A clear improvement method is still needed – Most confusion occurs when translating operational language into useful information for data scientists and translating data analysis back into operational contexts. A disciplined improvement methodology, with a clear objective, helps to avoid confusion and provide shared understanding regarding the improvement being sought.
Analysis should first be informed by process – Operations team members tasked with understanding and documenting a process (i.e., the subject of the improvement) need to be disciplined and thorough, avoiding the temptation to rush through it.
Field-based insights are valuable – For data scientists tasked with analysis, it’s essential they take time to understand the documented process. If possible, they should visit the work area and ensure they have a clear understanding of the questions that need to be answered through the data analysis phase.
Team diversity remains critical – The way teams deliver improvement hasn’t changed, even with the increased amount and quality of data now available. Teams still need to comprise diverse skills so they can balance detailed statistical analysis with field-based process familiarity.
Cross-team interaction is ongoing – During data analysis, interaction between operations and subject matter experts and data analysis teams needs to happen regularly. In some contexts, it can help to embed someone with operations experience in data analysis teams so they can practically translate information between project stakeholders.
Training the Force
In certain cases, plant modification projects aimed at improving throughput propagate from a poor original startup experience. The key to smooth startup is operations readiness, according to a paper titled, So You Are Investing in a Mining Project – What Usually Goes Wrong, written by Stephen R. Brown and Gilmore Tostengard of Performance Associates International, an Arizona, USA-based company specializing in mine and plant industrial training. According to the authors, money spent on operator training before a project starts up can pay big dividends in the years after, possibly making the difference between enabling a plant to reach design capacity quickly versus struggling for years to reach capacity and failing, then investing even more money to correct process problems.
Citing an almost 40-year-old study of mine-project startups conducted by Charles River Associates for the World Bank, the authors maintain that the study’s results are still valid today: Although 70% of mills and concentrators back then had an average annual production of 70% of design capacity during their first year, most of them went on to operate at 80% to 100% of capacity by the third year. However, more-complex process plants didn’t fare as well in the study. Even after four years, many of these plants failed to achieve design capacity, and several even failed before the fourth year.
According to the authors, operations personnel typically cite poor design and equipment problems as causes for project delays, but this approach masks a much more fundamental problem: an inadequately prepared workforce. An underlying fact that provided additional support for this premise was that the problem occurs in projects located in both developed and developing countries.
The combination of production shortfalls, lower than expected metal recovery, and the additional cost of subsequent plant modifications has a markedly negative impact on project cash flow after startup, according to the authors. They worked up a startup-scenario model for four hypothetical projects using identical capital cost, reserve, metal price, design production rate, tax and net present value figures, the only difference being the amount of resources assigned to workforce preparation. The scenarios encompassed a range of startup outcomes ranging from poor to fair, good to excellent.
Unsurprisingly, the projects that were modeled to invest little or no money and effort into workforce preparation fell into the fair and poor categories of startup success, respectively. The project model that invested a million dollars in worker training fared much better, reaching design capacity and recovery targets in the second year. And the project that spent more than $3 million on operations readiness had an excellent hypothetical startup, reaching design projection and recovery quickly — and reaping long-term benefits from having a knowledgeable workforce that is familiar with plant components and systems and can effectively troubleshoot process and control problems on their own.