BHP Billiton's multi-billion-dollar Jansen potash project under construction in September 2012 | Courtesy of BHP Billiton
BHP Billiton is not taking any chances with maintenance planning on what could become one of the world’s premier potash mines. Tens of millions of dollars
are at stake in potential unforeseen parts, labour costs and lost productivity over the life of the site. To minimize its maintenance risk, increase cost
planning certainty and test processes and equipment before they become entrenched, BHP Billiton has engaged consulting firm ARMS Reliability to perform
early asset reliability analyses for its Jansen project, situated 140 kilometres east of Saskatoon, Saskatchewan.
The goal of asset reliability analysis is to predict and then minimize lifetime maintenance costs and downtime, but by starting the process at the
prefeasibility stage rather than at the execution stage, the results can be implemented with more ease and less impact on cost. The information provided
will assist the BHP Billiton team in its plant design decision-making process.
“We were able to provide them with maintenance budget predictions, and also some production predictions,” explains Jason Ballentine, engineering manager
for North America at ARMS. “It’s not so much what we’re doing that’s unique. It’s the fact that they’ve applied it at very early stages of the project.”
The methods that ARMS Reliability and BHP Billiton are using for the Jansen mine are becoming increasingly common across the rest of the mining industry
but have been slow to be adopted in potash, partly because Jansen will be the first greenfield potash mine built in over 30 years.
Ballentine says companies fail to understand how asset reliability analyses can provide value early on in the process. “They’re sort of focused on
executing and getting the plant up and running, and they kind of forget about some of the long-term operability of the plant and the influence maintenance
can have on the actual production and the design,” he explains.
Once process flow sheets had been created in prefeasibility, ARMS began making reliability block diagrams (RBDs) using a powerful reliability simulation
tool. Preliminary process flow diagrams were used to model the relationships between the major pieces of mechanical equipment in the process. In one
section of the model, for example, material from a single wet sizing screen feed distributor is split into two paths, heading to another feed distributor
and a secondary feed distributor. From those two points, the material is routed to one of four wet sizing screens, each of which sends output material into
one of two secondary cage mills. Each component has a probability of failure associated with it. Simulations of the process were performed using this
detailed model; rough performance predictions could be made and capacity losses due to particular pieces of equipment quantified.
As the project progressed into the feasibility phase, process flow diagrams were revised, equipment selections were made, and equipment vendors were
chosen. ARMS began identifying the individual failure modes of the main process equipment. By the time the initial feasibility stage was complete, nearly
6,000 failure modes – specific ways equipment could fail – were identified in the process plant, and nearly 4,000 more below ground. For each failure mode,
a probability was assigned, based on a combination of manufacturer data, industry experience of the teams at BHP Billiton, as well as ARMS’ library of data
gathered over the last 10 years.
Planning and due diligence
The analyses informed the team about how much inventory they would need for spare parts, and will eventually let them know what their critical spares will
be. They also included major scheduled maintenance and generic maintenance tasks, and considered storage and surge buffers, which allowed ARMS to predict
the total availability of the plant and to verify that the plant would achieve its designed throughput capacity.
“Because we’ve considered all the possible maintenance failures, we’ve considered the maintenance outages, and we understand that it is possible to get
what we’re promising,” says Ballentine.
The solid data behind such predictions affords BHP Billiton an envious level of certainty in cost planning – plus or minus 15 per cent for maintenance
budgets and labour requirements at the feasibility stage. Ryan Posnikoff, BHP’s principal mechanical engineer for the project, says it helps the company
know what it is getting into: “It’s part of the puzzle.”