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TEAM GUARD · ERP

AI writes code. Robots do physical work. Who gives them the right task?

How people, ERP, AI agents and robots can work together in one production process.

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TEAM GUARD · ERP

Put one production process in order. Then automate.

How to define material statuses, responsibilities, deadlines and control points before configuring the system.

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Put one production process in order. Then automate.

Karen Arutyunyan · TEAM Method · EN
Contents

An enterprise has ERP. Documents are recorded, stock is visible and reports are generated. Yet production still calls the warehouse, the warehouse checks with the laboratory, and a manager manually decides whether the next batch can be used. The software works. The process still needs clear operating rules.

Why automation leaves uncertainty in place

Consider an incoming delivery. The warehouse records the quantity. The laboratory takes a sample, but the result is pending. Production sees the stock and plans to use it today. Everyone has completed a task, yet one shared rule remains undefined: does physical availability mean approval for use? Without that rule, ERP records the receipt but may not prevent premature release.

Start with one production flow

Choose a bounded flow, such as receiving raw material through approval for use. Identify its start, end, participants, documents and outcome. Follow an actual batch with the people involved. Observe waiting, phone calls, repeated data entry and decisions made when work is delayed. The first step does not require documenting the entire enterprise.

Separate availability from approval

Each batch needs an unambiguous status. A possible sequence is Received → Awaiting laboratory confirmation → Approved for use. A failed batch needs a separate status, such as Blocked. Names depend on the operation. The principle is that a warehouse receipt does not itself authorize consumption. Each transition needs an identified basis, supporting record and authorized person.

Assign responsibility for transitions

Saying that the laboratory owns quality is insufficient for managing a particular batch. Specify who samples, who confirms the result, who changes the status and who receives the notification. A responsibility matrix identifies the executor, decision owner and people who need information. When a decision is delayed, someone must be explicitly responsible for responding. Rules must match actual authority.

Set deadlines and exception rules

Critical steps need expected completion times grounded in the technology and available capacity. A delayed confirmation should trigger a defined response: notify the owner, escalate to the appropriate manager and retain the block. Urgent production demand must not become undocumented approval. Any permitted exception needs a reason, an authorized decision and a record of the outcome.

Where TEAM Guard fits

TEAM defines process architecture: roles, sequence, documents and rules. TEAM Guard defines acceptable boundaries and the handling of deviations. In this flow, controls may block consumption of an unapproved batch, monitor laboratory deadlines and flag attempts to bypass a required transition. The system performs agreed checks and signals deviations. An authorized person decides outside the established procedure, with the basis and outcome recorded.

Then specify the ERP requirements

The requirements can now be precise: statuses, permission rules, supporting documents, blocks and notification recipients. The technical specialist receives a specification that can be checked. Acceptance covers the normal flow and exceptions: a delayed result, a nonconforming batch and an unauthorized release attempt. Expected system behaviour is agreed before configuration.

What the pilot delivers

The deliverables are a process map, a responsibility matrix and ERP control points, supported by status rules, deadlines and exception procedures. The enterprise reviews these before software configuration. Success is assessed through selected measures such as decision waiting time, manual clarification counts and consumption without approval. Financial impact is calculated from observed data rather than promised in advance.

A pilot covering one flow

A bounded pilot makes the approach reviewable. The pilot price is €2,400 excluding VAT, covering up to five interviews. Travel expenses and ERP configuration are excluded. Flow boundaries and deliverables are agreed before work starts.

ERP exposes the business system. Define how one process should work first, then automate the agreed logic.

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AI writes code. Robots do physical work. Who gives them the right task?

Karen Arutyunyan · TEAM Method ·

How people, ERP, AI agents and robots can work together in one production process.

Individual operations are easier to speed up. An AI agent can gather data and propose a decision, software can check conditions, and a robot can move a part. The result for the enterprise depends on how those operations fit together. Who assigns the task? What data authorizes action? Who makes the decision when the process deviates from the plan?

What is changing in technology

OpenAI is developing its Agents API to support long-running tasks, tool use and work shared across agents. Microsoft examines how agents fit into the entire software delivery lifecycle, from defining the task to checking the result and collecting feedback.

Google DeepMind’s AlphaProof Code illustrates the value of a precise specification. Agents help write it and build a mathematical proof that the implementation meets it. Lean checks the proof. If an important requirement is missing from the specification, it falls outside the scope of verification.

In robotics, these decisions have physical consequences. In a Google DeepMind and Apptronik pilot, the Apollo 2 robot kitted automotive parts at a Mercedes-Benz factory. NVIDIA develops Isaac GR00T for robot training and evaluation, and Boston Dynamics designs Atlas for industrial operations. The enterprise has to decide in advance how a particular robot action fits into the production flow.

A manufacturing example

Consider a kitting station. Before the shift starts, parts from an eligible lot must reach the production line. ERP shows stock on hand, but some lots are still awaiting quality release. Given the instruction “pick the parts from the warehouse,” a robot could move a lot that is physically available before it has been cleared for use.

In TEAM, the task is defined through the conditions of the process. ERP supplies the requirement and the lot status. Software allows only released lots to be picked. An AI agent flags the risk of a delay and proposes a substitute from among the released lots. The robot receives a confirmed task and reports completion. If no eligible substitute is available, the responsible employee decides whether to reschedule production.

The role of TEAM Guard

We start by designing the enterprise architecture and defining how work is performed at each station. For every step, we specify who performs it, what data it needs, what outcome it must produce and when the work can pass to the next step. TEAM Guard defines deadlines, permitted deviations, prohibited actions and the points where a human decision is required. ERP connects these steps to orders, lots, statuses and recorded outcomes.

The enterprise can then measure the effect of automation on the whole process. Are fewer parts deliveries to the line delayed? How many lots were issued in error? The desired operational result guides the decision about which work to give to software, an AI agent or a robot.

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