Location-based process automation benefits
Leveraging location-based process automation technology for autonomous operations can help manufacturers in many ways.
Manufacturers, suppliers, and logistics companies are finding themselves at an interesting intersection today. Digital transformation, forcefully propelled atop any executive agendas by COVID-19, is no longer a trend or a hype. With more pressure from stakeholders, customers, and competitors, companies need to act fast and decidedly to kickstart their smart factory roadmap.
While there is vast consensus on the need for digitalization – around 70% of manufacturing organizations in the US and Europe have adopted a digital transformation (DX) strategy – the enormity and complexity of the transformation at hand are crippling to many.
Finding the right strategy
In identifying the best approach to digitize their operations, companies often fall short of capturing some of their most powerful insights: information on the location and dynamics on their shopfloor and supply chains, such as assets and vehicles. As the baseline data for analyzing, optimizing, and automating processes, location-based automation is the key to unlocking cost reductions, quality improvements, and speed increases in production and supply chain. But how can companies truly leverage the data captured by location technologies such as GPS, UWB, BLE or RFID? Location-based process automation (LPA) systems, a new software category, might be a viable option.
“Location data is the foundation for any meaningful industrial automation,” says Mehdi Bentanfous, global industries lead at Kinexon. “Moving assets make up 99% of all activity on the shopfloor. It is an incredible competitive advantage to utilize this knowledge on where assets are at all times, which process steps they went through, and how long they took along the production line.”
To unleash the value a central operating system for all moving things can create, LPA should fulfill certain criteria and provide a set of key features, including low-code/no-code interface, technology- and vendor- agnostic integration, as well as powerful and forward-looking automation customization opportunities.
Three barriers to digitalization
Since the introduction of the concept, Industrial Internet of Things (IIoT) applications have emerged as one of the key strands of digital transformation. Per a Deloitte study, 72% of companies regard IoT as the most central opportunity in digitalization. While most companies understand the essential need to act upon digitalization to increase their revenue (59%), improve their risk management (27%), and reduce costs (29%), the disruptive potential of new technologies still goes unused. Why has the adoption of IIoT been so relatively slow when compared to smart applications in consumer devices, especially when the benefits are widely known?
Deloitte identified three common barriers to digitalization in manufacturing and logistics in their study:
- A lack of transparency regarding profitable, customized solutions
- A lack of digital competency inside and outside of IT
- The complexity of transformation processes.
While manufacturers have digitized large parts of their machine parks by now, a striking data gap has become evident: To achieve the goal of end-to- end automation data is required from all parts of the production process, not just machinery. To achieve this, companies are utilizing localization, a process that performs physical measurements like angles or distance to find the accurate position coordinates of objects. The inclusion of location data in IIoT applications allows companies to gain transparency, optimize, and automate processes via an entirely new software category: location-based process automation systems.
According to Dresner Advisory, around 80% of enterprise data currently have a location component, which bears tremendous potential for value-adding IoT applications. The versatility and relative ease of implementation make location-based process automation systems an attractive solution for companies.
Original content can be found at Kinexon.