We’ve been using EFFECTO dashboards for over five years and it really has made our short- and long-term decisions a lot easier.
Case study : JM Champeau, Canada, Quebec
You can act with confidence when you have reliable data.
A family-owned and dynamic company
J.M. Champeau is a family-owned hardwood-processing business located in the Eastern Townships of Quebec just a stone’s throw from the American border.
The 225 employees on the teams at our St-Malo and Frontenac plants transform premium-quality wood into top-of-the-line products to meet the specific quality criteria our customers demand. Our total output averages of 25 MMBF a year.
Need more than a "feeling”
Because our saw line includes several pieces of equipment that don’t have advanced dashboards, the machines don’t talk to each other, so it’s up to us to identify improvement priorities or the main causes of downtime. There’s always an element of uncertainty in our decisions since they’re sometimes based on preconceived ideas or even just a gut feeling for identifying urgent problems or bottlenecks. With data, there’s never any doubt. So, naturally, we wanted to integrate digital systems into our plants to automate and simplify data access.
The first challenge was to get equipment from different generations to talk about
We have several generations of equipment using very different technologies, some very recent, others much older. Since the old equipment was working well, we didn’t want to change it, so the major challenge of the project was to collect all the data from all our machines and analyze it. Our equipment suppliers know a lot about their machinery, but they’re not specialists in creating advanced dashboards for them. Especially when the data comes from different generations of different machines from different OEMs.
Our first attempts were inconclusive. In collecting data from each machine and finding a way to cross-reference the machines, we had to compromise either on accuracy or on the time period analyzed. While each machine generates data, it’s really hard to put all the data together to get an overall big picture. Another problem was that everything was done manually. It took a lot of time to get results that were never up to our expectations.
