Smart factory transformation starts with the production problems worth solving. Connect machines, people and business systems to make losses visible and improvement measurable.
A plant does not become smarter by adding more dashboards. Production teams need consistent definitions, reliable events and a clear response when performance changes. MetaDynamic helps define the use cases, architecture and rollout plan that bring these pieces together.
Start with one line, one constraint or one recurring loss. Establish a baseline, validate the data and demonstrate a repeatable operating process before extending across the plant.
Review production workflows, system boundaries, manual records and data gaps with plant and IT teams.
Agree availability, performance and quality definitions; capture downtime reasons and make improvement actions traceable.
Bring equipment events together with work orders, shifts, products and operator context.
Design reliable exchanges for production orders, consumption, completion and quality status.
Prioritise inspection, condition monitoring and traceability around the cost and impact of failure.
Create reusable standards while allowing for different equipment, products and operating practices.
Choose a small set of operational measures that teams can act on. Every indicator needs a definition, a baseline and a named owner.
Understand unplanned stops and the time lost between operations.
Compare actual throughput with an agreed product-specific reference.
Track good output, scrap and rework with consistent event capture.
We define the systems, equipment and delivery responsibilities in scope before implementation. The engagement plan identifies what will be tested, who accepts the result and how the solution will be supported.
A smart factory connects operational data, production processes and business systems so teams can monitor performance and respond with better context. The scope can begin with a single production line.
Not necessarily. We assess available interfaces and the practicality of adding sensors or gateways. Unsupported equipment and critical control functions need a separate engineering review.
Agree a baseline and acceptance measures such as downtime classification, production reporting effort, first-pass yield or traceability coverage. Improvements must be established from operating evidence.
We assess integration with SAP, Microsoft Dynamics, Infor or other systems against the available interfaces, data ownership and transaction requirements.
Tell us where production loses time, information or control. We will help identify the right first use case.