CHEMICALS & PHARMACEUTICALS
CONNECTING THE CONTROL AND ENTERPRISE LAYERS
Veerabhadra Rao Sigireddi, Subject Matter Expert – Manufacturing Systems & Shopfloor Integration, InspireXT Consulting, discusses the benefits of connected shopfloor architectures
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n pharmaceutical and life sciences manufacturing, strict regulatory frameworks demand complete batch genealogy, validated processes, and robust electronic records. In food and beverage production, allergen
control, traceability, and yield optimisation are constant priorities. In chemical processing, tight process control and early drift detection are essential to prevent off-spec product and downstream losses. However, traditional system architectures such as DCS, PLCs and ERP systems separate these operational layers: This separation introduces persistent engineering challenges such as: • Delayed deviation detection, particularly in batch-based operations
• Fragmented data landscapes, requiring manual reconciliation
• Limited real-time material genealogy, especially during rework or blending
• Heavy reliance on post-batch reporting for decision-making In highly regulated sectors such as pharmaceuticals and life sciences, these delays affect not only efficiency but also batch release timelines and audit readiness. A connected shopfloor architecture establishes a
structured digital bridge between physical process execution and enterprise systems. Rather than transferring large volumes of raw signal data, the focus shifts to transmitting structured execution events that reflect actual production states. A typical architecture comprises: • Control systems (PLC, DCS, SCADA) managing real-time process stability
• An edge integration layer that aggregates, filters, and contextualises signals
• Enterprise ERP platforms that receive structured production, quality and maintenance events In process industries, edge integration is particularly important due to high-frequency signals and strict validation requirements. Edge systems: • Interface directly with industrial communication protocols
• Apply contextual logic to convert control signals into production-relevant events
• Filter non-essential data to prevent overload of enterprise systems
• Maintain secure and segmented communication pathways This approach preserves the autonomy and safety of control systems while enabling real-time enterprise visibility. For example: • In a pharmaceutical batch operation, equipment state changes, material additions, and quality checkpoints can trigger structured updates to enterprise systems.
28 Manual reporting (left) and a connected shopfloor solution (right) - Conceptual AI-generated image
• In food and beverage production, allergen changeovers and cleaning validation states can be synchronised with material and scheduling records.
• In chemical processing, deviations in critical parameters can be escalated as structured production events rather than remaining isolated within the control layer.
• Condition-based maintenance in process environments: Equipment health signals are collected directly from shopfloor assets through the control system and passed through the edge integration layer.
When these signals exceed defined limits or indicate early signs of wear, a maintenance event is automatically sent to the ERP system. This can trigger a maintenance notification, work order, or inspection request.
In pharmaceutical and food manufacturing, this ensures maintenance activities are properly recorded and traceable for compliance purposes. In chemical plants, it helps prevent unplanned downtime by allowing maintenance teams to act before equipment failure impacts production. Process manufacturing rarely follows a linear
flow. Materials may be blended, split, reworked, quarantined, or conditionally released depending on in-process testing. Effective digital architectures therefore prioritise:
• Dynamic material genealogy, updated during execution
• In-process quality status visibility, not solely final inspection results
• Campaign and batch state awareness, including transitions and holds
In pharmaceutical and life sciences facilities, this capability strengthens data integrity and supports
PROCESS & CONTROL ENGINEERING | APRIL 2026
electronic batch record accuracy. In food and beverage environments, it improves recall readiness and traceability speed. In chemical plants, it enhances early identification of off-spec trends and yield loss mechanisms.
The key engineering principle is alignment between digital models and real process behaviour. Oversimplified execution models can undermine traceability and compliance. Successful implementation in process industries depends on disciplined engineering design. Critical considerations include: • Model fidelity • Signal prioritisation • Operational usability • Cybersecurity and segregation • Resilience
Edge-based architectures should allow
production to continue safely during temporary network or cloud interruptions, particularly important in continuous chemical processes or high-value pharmaceutical batches. When execution, quality, and material status are
synchronised in near real time: • Deviation response times shorten • Cross-functional collaboration improves • Batch review cycles are reduced • Process drift can be addressed before yield is compromised
For the pharmaceutical and life sciences sector this can directly influence batch release timelines, for food producers it supports waste reduction, and for chemical processors it enhances operational stability and throughput predictability.
InspireXT Consulting
inspirext.com
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