Market advisory firm ABI Research says that because manufacturers need to ensure the success of programs while dealing with restricted travel and distributed teams that select digital transformation initiatives have gained momentum in terms of their adoption and potential. These include cloud for collaboration and synchronization across teams and departments, digital twins for monitoring and maintenance and analytics and AI for system-wide, software-driven automation. ABI's latest suggest that in the quest for digital transformation, manufacturers and industrial firms will spend $19.8 billion to transform and support IIoT data analytics value chains by 2026, up from $4.92 billion in 2020.
These findings are from ABI's Industrial and Manufacturing Semiannual Update report.
"Future factories are expected to have flexible and adaptable manufacturing lines that operate with greater autonomy, integrated closed-loop quality control, and connected workers to improve effective response to changes in supply and demand as they occur," said Ryan Martin, research director at ABI. "The reality is that most manufacturers did not have these capabilities going into the pandemic. Yet today technologies like cloud, simulation and SaaS are viewed as table stakes."
ABI notes the strategic partnership between Siemens and SAP, PTC’s acquisition of Arena Solutions, Aveva’s acquisition of OSIsoft, Emerson’s pick up of Open Systems International and the encroachment on smart manufacturing platforms by hyperscalers AWS and Microsoft Azure. Companies such as Autodesk, Dassault Systèmes, PTC, and Siemens continue to double down on cloud and SaaS.
"Digital maturity is measured in five levels," said Martin. "These levels span human-controlled and early automation to full, lights-out manufacturing. Most manufacturers are at level 2 or 3; they have started to connect some assets and see the benefits of digital transformation but haven’t fully scaled. Levels 3 and especially 4 and 5 are where technologies like wireless connectivity, IoT platforms/suites and AI become critical for both monitoring and closed-loop quality automation and process control."
