Last Updated on April 8, 2024 by Team Experts

We’ve combined this eight-step procedure from this month’s of Plant Engineering to help you find and debug your process control system with Industrial automation, which may be developed and used over time. You may get the correct concentration on a single system or process by beginning with little more than a pencil and paper and using some readily available tools.

1. Plot the process

Make a graph of the system of intrigued and its main forms to begin. A “back of the envelope” drawing that explains the key system processes will suffice for now, even if you might later wish to use a drawing application like Visio.

2. Identify key components

Next, note the important components of each process. The key elements will differ depending on the industry, but you should think about things like motors, variable frequency drives, sensors, and power supply for many industrial processes.

3.  Assign metrics for key components

Select some “operational metrics” for each of the imperative components you specified within the previous step. These are things you can measure that provide you important details about how the component is doing. 

Data about a component that can be measured basically and for which information can be collected at a single point in time are great candidates for metrics (for example, meter estimations, waveform captures, observations, and photographs). Get significant quantitative information (such as a temperature measurement) or subjective information (for case, the shape of a waveform from a variable speed drive).

4. Take measurements

The major component metrics should be measured and recorded. It doesn’t have to be a difficult process to collect this data. You’ll be able to begin with a pencil and paper indeed in spite of the fact that you’ll afterward wish to record and look at component metrics in a spreadsheet or database.

The greatest resource for determining what to measure and how to measure it is your experience and training, but here are some straightforward “rules of thumb” for taking measurements that are both accurate and efficient. Beginning your measurement at the power source, track the current as it flows.

5. Create a data “dashboard”

In spite of the fact that statistical data, just like the one you obtained in step 4, may be a capable tool for analysis and forecast, translating rows and columns of unprocessed information can be challenging. Making an advance decision on the range of values for each measure that constitutes OK, suspicious, severe, and extreme is an efficient strategy to cope with this type of data overload.

Data ranges enable you to build a simple, color-coded status for each system component that you can display in a spreadsheet, whiteboard, or notepad. Data analysis and decision-making for complex systems can be made possible by the resultant simplified, high-level perspective of the system that is free of distracting detail.

6. Prioritize components for attention, maintenance, and budget

You may now prioritize which components of the system require your attention based on your clear and uncluttered view of their current state.

7. Make the decision

Decide what to do next for each component on your prioritized list: Does it require repairing (for instance, resizing the conveyor’s motor to manage the load demand better)? Does it need to be replaced? Is it best to simply keep an eye on it? 

Another choice is to just let it fail while making plans in advance and allocating funds and resources. The decision-making process can be enormously helped by objective, prioritized data on key components.

8. Refine and extend, but stay flexible

Once you have got a successful strategy in place, you’ll be able to continuously improve and extend it. Be beyond any doubt to keep flexibility in intellect when your system approach changes. Your system approach will be able to adjust when processes, components, priorities, and your needs change if you collect data using a range of general-purpose, handheld tools. 

Among the questions to make are: Are there more processes or components that should be included, and will picking different or additional metrics improve your strategy? Do you need to spend more money on new equipment, training, or personnel in order to properly implement the plan? Should your system diagram be more detailed or better providing? Do you wish to spend money on more effective analysis and storage tools, such as spreadsheets, databases, or programs?

A Strategy for the Long-Run

Plant managers are better capable of utilizing their limited resources, such as time, budget, equipment, and personnel, when they have an accurate, clear, and controllable understanding of a system’s essential processes and key components. The hard data you collect may also be used to support workforce increases, equipment purchases, and process adjustments.

The time and effort needed to create and maintain an effective system strategy will pay off in more effective decisions, in time and money saved, and in the peace of mind that comes from knowing both where you stand and where you’re going next. This is true whether you start small and keep it simple or jump in and develop a detailed strategy with hundreds of metrics managed in a computerized system.

Read more: A Handy Guide to Manufacturing Industry 4.0 for Plant Managers