Automated work cells: 3 steps to improve ROI

You’ve been hearing about automation, robotization, and going digital for years now. But the question you should really be asking is “How do I leverage data from newly automated work cells?” It’s time to connect the dots and take a look at the big picture. Merkur has a simple 3-step strategy for understanding what your equipment is trying to tell you about your operations: understand the story, speak the right language, and make the most of your new relationship with your machines.

1. Understand the story

The first step is to understand all the factors critical to achieving the automated cell’s objectives. It’s important because it helps you hone in on the most important and urgent messages the cell is sending.

You have to link up your data strategy with production quality, which, in turn, is tied to the profitability objectives that led you to automate the cell in the first place. Your cells can then be optimized using a range of simulation techniques that anticipate production issues. Assessing operation simulations, technological risks, and productivity losses involving the automated cell gives you the full picture.

2. Speak the right language

Automation projects generate huge streams of additional data from new sources, including machines, systems, sensors, and more. It’s very difficult to use and interpret raw data because machines on the production floor often speak different languages. Step two helps you interpret your data properly to improve quality.

A good data management strategy differentiates between edge computing (processing information close to the cell) and data archiving (local or cloud-based). It’s a matter of capturing, processing, transforming, and collecting data in the right place so it provides a clear view of events in the automated cell.

Once a good data management strategy is in place, it’s time to address communication. Each workstation and hierarchal level requires a different version of your data. For example, a machine operator may only require minimal data related to their workstation, while the floor supervisor will want it to sync up with their planning. Each employee on the floor needs to understand the data that is relevant to them and allows them to identify anomalies as soon as they occur. Management, for its part, will likely want to get macro data on a periodic basis rather than drowning in reams of data that is only relevant to the floor.

The same machine-based raw data needs to be translated differently for manufacturing, operations, and decision-making purposes. Your machines have secrets to tell, and they’re relevant to people at every level of your organization.

3. Make the most of your automated cells

In order to take full advantage of your automated cells, you need to understand the fundamentals and mechanics of getting the right data to the right people at the right time. The key is creating connections that use and process relevant data only. These connections will eventually be used to create custom dashboards. This step requires considerable technological expertise and a firm grasp of your needs. That’s why it’s a good idea to hire professionals.

A qualified partner will be able determine the best way to decipher the story. It requires expertise in four types of engineering: electrical engineering, computer science, business intelligence, and operational excellence. Merkur has all the bases covered. We’re a strategic partner that can help you decode YOUR story!

Proper data management means you make better decisions faster. And agility and responsiveness are synonymous with competitiveness and profitability. In today’s fast-paced world, a productive data strategy is an absolute must.

Marc-André Cyr, Ing.

Directeur de programmes et Solutions Numériques

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