Robotic Automation has made a marked impact on the manufacturing industry. Plant managers can now re-distribute their human workforce towards performing more valuable tasks like setting up new machines, writing PLC programs and assembling parts simply by enlisting a robotic workforce to handle repetitive and dangerous jobs. This helps companies to leverage the skills of their employees better and also create meaningful employment opportunities.

But it must be stated that automation technology does not guarantee immediate profits, with automation successful and accurate integration is vital. Here are a few main principles to follow for success and proper integration of the robotic automation process.

Data Integration

The image when talking about automation in most people’s minds brings up visuals of multiple robotic arms moving simultaneously to assemble products on an assembly line. While the image does hold a lot of truth, it is really only half what automation really is.

Even though robotic automation relies on physical hardware to execute tasks, it is almost as much if not more reliant on information. After all, automation would become quite difficult if it did not have access to data that was input analyzed and processed by the system. However, the difficulty lies in obtaining this data. Quite often, when factories or manufacturers are changing their operations to include more autonomous equipment, the operational data required for integration is inaccurate or stored across a differing system that cannot be shared with one another.

Unfortunately, starting from scratch or replacing these systems tends to be quite expensive and acts as a barrier for businesses to enter the world of autonomous operations. For successful integration and deployment of robotic automation, the automation process requires access to any data collected by any device associated with the workflow. Once this process is finished, the conclusive new information must be updated on those same systems as well as any connected devices to ensure that all records are up to date.

Intelligent Automation

Once there is proper access and analysis of all relevant data, an expert technician can start developing the required automation process. In the case of manufacturers, these technicians develop code(on top of maintaining and troubleshooting the system) to automate tasks that are high volume and repetitive or have a high chance of human error.

Contrary to belief, automation was not created to replace human reasoning and intuition. However, it must be noted that using robotic process automation(RPA), several tasks can be effectively completed if it was developed using the hard data collected and the accurate application of programming logic. Collecting and accessing data from various systems and connecting that data to program intelligent RPA are two separate processes. The drawback to this whole process is that it tends to take a lot of time and effort initially to collect and analyze the data sets and develop the automation code based on it but the immediate and noticeable increase in efficiency alone makes the whole process worthwhile.


The best approach for manufacturers who are new to this transformative technology is the same taken when exploring the viability of any new technology. Before committing financially to integrate automation throughout the operation, it is wise to test the process on one project as a proof of concept. Similarly, any technician willing to gauge the viability of a new career in building or servicing robotics and AI technology should understand and be clear with the readiness of the managers in adopting RPA in their industry. The project must consist of small and contained test runs in short order where the cost relative to benefits analysis can be conducted easily and quickly. If the process is not tested in real-world conditions, it becomes difficult to gauge what the return on investment will be.

One more benefit of beginning with a test project as a proof of concept is that it might address many of the questions and doubts regarding the scalability with regards to the integration of RPA. Specifically, how pitfalls specific to the business or industry can be avoided as well as how the technology can be more efficiently leveraged to increase productivity for the manufacturer while creating opportunities for the employees.

The best approach when integrating automation technology is a two-pronged approach. The first should be modular so that it is easy to maintain the system. The second consists of flexibility(that means that the RPA should be robust enough to apply more complex algorithms as required when the quantity of data increases exponentially.