Open Automation in Process Industries: Transition from Proprietary DCS to Software-Defined Control Systems
Mohammed Hazique Shaikh
Mohammed Hazique Shaikh, Department of Industrial Automation & Engineering, 161 Mechanic Street, Bellingham (MA), United States of America (USA).
Manuscript received on 30 April 2026 | First Revised Manuscript received on 06 May 2026 | Second Revised Manuscript received on 10 May 2026 | Manuscript Accepted on 15 May 2026 | Manuscript published on 30 May 2026 | PP: 1-7 | Volume-15 Issue-6, May 2026 | Retrieval Number: 100.1/ijitee.E127115060526 | DOI: 10.35940/ijitee.E1271.15060526
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Industrial process control has relied on proprietary DCS for over five decades. The model worked. But working and working well are different things, and in 2026, the gap between what proprietary DCS delivers and what operators in manufacturing, oil and gas, chemical processing, and water treatment need has grown wide enough to drive real change. Vendor lock-in, hardware obsolescence that stretches across decades, and maintenance contracts that give a single supplier complete leverage over upgrade decisions are no longer tolerable when the alternative, open and software-defined control, has been proven at an industrial scale. The Open Process Automation Standard (O-PAS), the IEC 61499 function block model, and OPC UA connectivity together provide the technical foundation for software-defined control systems (SDCS) that break these dependencies. Documented lifecycle cost savings reach approximately 52% over twenty-five years when compared to equivalent proprietary DCS platforms. This paper reviews the standards, examines real deployments, and confronts the barriers that still slow adoption, particularly the near-complete absence of IT-domain competencies in OT workforces. An original Software Defined Automation Risk Mapping Model (SD-ARMM) is proposed, providing practitioners with a five-dimensional, risk driven tool to determine which migration strategy fits their specific organisational and operational reality.
Keywords: Terms: Open Automation, Software-Defined Control, DCS Migration, IEC 61499, O-PAS, OPAF, Process Industries, Distributed Control Node, IT/OT Convergence, Risk Mapping, SD-ARMM, Industrial Digitalisation, Vendor Lock-in.
Scope of the Article: Industrial Engineering