Managing State in Modern Manufacturing Systems

Managing State in Modern Manufacturing Systems

In today’s modern manufacturing landscape, data flows across an increasingly diverse technology stack, including systems like ERP, SCADA, IIoT devices, cloud analytics, AI platforms, MES, and more. Each captures a different view of what’s happening throughout production. Though without a shared understanding of state, systems and processes can become out of sync.

State is the foundation of execution, compliance, traceability, and analytics. Yet, many times, state is managed inconsistently or redundantly across systems, creating conflicting definitions and understanding of production.

This piece delves into why state matters, why centralized state management should be a core capability of your MES, and how TrakSYS implements state machines to enforce event-driven automations across the enterprise.

Managing State: The Overview

This video provides a quick introduction to managing state in manufacturing environments: what states look like in workflows, how state machines define allowable transitions between states, as well as what this all looks like in TrakSYS.

Interested in learning even more about the intricacies of state management and how to govern it within your MES? Keep reading.

What is “State” in Manufacturing

In the context of manufacturing, “state” is the current condition or status of a business object (item, entity, batch, task, etc.) at a moment in time. It answers questions like:

  • Is this order running or on hold?
  • Is this tank idle or in CIP?
  • Is this batch approved, rejected, or quarantined?
  • Is this workflow step pending or complete?

Each entity across production has a series of states to describe its status. Here are some common examples:

Entity States
Production Orders Planned → Released → Running → Complete → Closed
Equipment Idle → Running → Setup → Down → Maintenance
Materials & Lots Received → Quarantined → Released → Consumed → Scrapped
Tasks & Approvals Pending → Assigned → In Review → Approved → Rejected

A state may just seem like a label, but it drives business rules, system behaviors, physical actions on the plant floor, and communication between systems. Thus, without consistent state definitions, systems won’t agree and can lead to incorrect scheduling, inaccurate OEE, failed audits, misinformed decision-making, and more.

The Common Problem: State Drift

Without a clear state management strategy or system in place, each system can define state independently, for example:

  • ERP determines the financial lifecycle of orders
  • MES defines the execution lifecycle
  • SCADA specifies machine tag values
  • LIMS manages quality disposition
  • CMMS tracks the maintenance lifecycle

When each of these systems has its own models, there is no centralized source of truth for state and transition definitions. This can cause “state drift,” where systems disagree about the reality of an object’s state.

State drift can result in a range of miscommunications, including:

Issue Example Impact
Conflicting statuses ERP says Closed, MES says Running Bad costing and incorrect KPIs
Inconsistent machine states Each line codes downtime differently Inaccurate or lack of root-cause analytics
Redundant scripting Each system redefines logic More time spent on script maintenance
Manual mapping between apps Integration per interface Slow deployment

The Solution: Centralized State Management in MES

The solution to state drift is a centralized state management system. A unified understanding of state ensures that all systems reference a standardized source of truth with consistent definitions, rules, and transitions. This can be achieved with an MES—with tools like TrakSYS State Machines.

MES is the right place to own and manage state because it acts as an execution layer for your technology stack. It’s close enough to machinery to capture real-time transitions, yet also aligned with business systems, which enables a holistic, enterprise view. This positioning, plus its knowledge of operational context (order, material, equipment, personnel, quality, etc.), allows your MES to track and act on state.

For example, when an order moves to Running, TrakSYS can release materials, update OEE, start data collection, trigger compliance workflows, and notify external systems. Or, when equipment moves to Down, TrakSYS can classify root cause and initiate maintenance workflows.

Using TrakSYS to unify and manage states can result in:

  • Standardized deployments by offering standard, preconfigured models that can be reused across sites
  • Better operational discipline with readily available, software-enforced SOPs
  • Reduced validation efforts due to less custom code to review
  • Improved KPI accuracy by eliminating conflicting running and downtime states
  • Stronger compliance and regulatory readiness with detailed logs of transitions and approvals

Conclusion

State management may not be the first thing that comes to mind when contemplating how to streamline your operations. However, it’s undeniable that state is a core pillar of digital manufacturing.

When fragmented across systems, misaligned states erode data integrity, compliance, and process control. When centralized—particularly within an MES—proper state management becomes the engine that drives consistent execution, automated workflows, accurate analytics, and enterprise-wide standardization.

TrakSYS State Machine can deliver centralization capabilities in a configuration-driven, integrated, and auditable way that fits seamlessly into modern manufacturing operations. Interested in learning more about how our MES can help you manage state? Contact us today.

FAQs

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