- Industry: Six Sigma, Mining
- Product(s): DecisionTools Suite
- Application: Six Sigma Design of Experiments
Metallurgical giant Met-Mex Peñoles uses the DecisionTools Suite for Six Sigma Design of Experiments. Because silver and gold are so expensive, process optimization allows analysts to test innovations, avoiding costly trial runs.
When you are working with silver and gold, pilot projects to test innovations in the manufacturing process are very costly—and risky. Using @RISK to simulate changes in process design allows us to answer some difficult questions without actually running trials of the process.Ignacio Quijas, Technology Manager, Met-Mex Peñoles
DecisionTools Suite in Six Sigma Design of Experiments
Because of the costliness of its raw materials, the metallurgical giant Met-Mex Peñoles, the world’s largest refiner of silver and Mexico’s largest refiner of gold, tries to avoid expensive pilot projects. To cut down on the number of trial runs, the company simulates the refining process by using the DecisionTools Suite in Six Sigma Design of Experiments. This allows the company to work on process optimization and sacrifice a minimum of gold and silver to its experiments.
According to Ignacio Quijas, technology manager for Peñoles, “When you are working with silver and gold, pilot projects to test innovations in the manufacturing process are very costly—and risky. Using @RISK to simulate changes in process design allows us to answer some difficult questions without actually running trials of the process.”
To offer some perspective on the exacting standards Peñoles must meet, Ignacio points out that, for instance, a 100-ounce silver bar must weigh at least 100 ounces—however, the price of the bar does not increase if the bar weighs slightly more than the specification. The additional silver is simply passed along free to the customer and is a production cost.
Each step in the manufacturing processes for gold and silver value-added products creates room for additional error, and the way Peñoles optimizes its process is to reduce the variability of the errors across the manufacturing steps. To build its Six Sigma simulation, Peñoles inputs the physical measurements of the errors and also feeds into the model the specifications and tolerances of its manufacturing equipment, different physical operations, random processing errors, and cost analyses that are pinpoint precise. “We are measuring the amount of gold an silver that turns up when we do every operation and can result in loses,” Ignacio reports.
His primary simulation tool is @RISK. “The functionality gives you so much more vision.” But because of the need for precision in his simulation, Ignacio also makes extensive use of @RISK distribution fitting and TopRank. He likes their capacities for graphic representation, which he uses to explain the intricacies of his simulations to colleagues.
“The ability to communicate aspects of the simulation is important,” he says, “because these very detailed models serve the same function as early trial runs.”
Yes, he said, Peñoles does still rely on pilot projects, but only after DecisionTools has accounted for every speck of silver and gold that might result in the production losses or recycled materials that increase cost.