Factory automation and equipment integration
We connect data from PLCs, sensors and existing equipment to improve visibility and reduce staffing requirements.
Manufacturing Knowledge AI and Drawing Search: Turn Expert Skills and Historical Assets into Actionable Knowledge for Every Employee
Rather than adding equipment, cameras, PLCs and robots as isolated improvements, we start with automation and physical AI that can be tested in your current process. The aim is to reduce inspection workloads and stabilize operations, not simply to create a demo environment.
The Challenges of Reliance on Individuals and Knowledge Transfer in Manufacturing
We connect inspection, robots and existing equipment data to reduce staffing requirements and missed defects together. Our aim is not to create a demo environment. We examine where people are held up in the process before defining what to connect.
Visual inspection
AI cameras detect defects to reduce inspection workloads and missed defects.
Robot systems integration
We support robot-arm installation, control and integration with peripheral equipment.
Three Core Benefits of CREA Manufacturing AI
We distinguish between measures that help current lines, such as visual inspection and digital kanban, and future implementations such as digital twins and humanoid robots.
Digital twins
We reproduce equipment and processes digitally to accelerate validation of improvements.
Digital kanban
We digitize paper instructions to make progress and inventory flows visible.
Bin picking
We use robots and image recognition to help identify and pick randomly placed parts.
AR / VR
We overlay information visible in the workplace to support work instructions, training and remote assistance.
Humanoid robots and physical AI
We support research, proofs of concept and implementation studies for AI that operates in physical spaces.
Sensor integration
We collect temperature, vibration, position and other data for anomaly detection and maintenance.
Test small, and verify on real equipment.
We do not ask you to make investment decisions from concept diagrams alone. We assess accuracy and operational workload with real data and equipment, then implement the solution, including safety and peripheral equipment integration.
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Workplace assessment
We review processes, equipment and constraints to identify what can be automated.
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Proposed approach
We define the combination of cameras, robots, PLCs and existing equipment.
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PoC
We assess accuracy and operational workload with real data or equipment to inform your implementation decision.
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Implementation
We implement the solution, including peripheral equipment, safety and connections to existing systems.
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Adoption
We adjust the solution to how your teams work, helping stabilize inspection and operations.
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Maintenance and expansion
We continue supporting process changes and subsequent automation initiatives.
Use testing to gather the information needed for a deployment decision.
We first define the process to automate, the scope of equipment connections, and the conditions to test. The proof-of-concept results help distinguish what can proceed to production from what needs further validation.
System configuration and connection scope
We define the roles of cameras, robots, PLCs, sensors, and existing equipment. We specify the data and signal connections and determine the scope of mechanical, electrical, and software implementation.
Accuracy and cycle time
We define checks for each process, such as distinguishing acceptable and defective products in inspection or measuring robot cycle time. We use actual data or equipment to test whether the proposed approach can meet site requirements.
Stop conditions and on-site operations
We review how people move through the work area, equipment stop conditions, and signal coordination with surrounding equipment. We define production operations, including the effort required for operator checks and recovery.
Discuss a Proof of Concept Using Your Actual Drawings and Data
You can consult us before the scope is fully defined. We use the process information available to identify what to investigate during the site review or proof of concept.
The target process and equipment
We review the process flow, equipment and PLC specifications, layout, and available signal connections. We also ask about requirements for retaining current equipment and its relationship with adjacent processes.
Actual data and physical samples
We review materials such as photos of inspection targets, examples of acceptable and defective products, parts to be handled, and sensor data. We discuss which materials are needed and what can be shared for each project.
Operating and working conditions
We ask about process cycle times, production volumes, available equipment downtime, and tasks that involve people. The conditions for testing on site determine the validation method and deployment approach.
Distinguish implementation scope from ideas that need validation first.
Improve existing processes
We consider approaches for current processes, such as equipment and PLC connections, visual inspection, and digital kanban. We agree on the implementation scope after reviewing site conditions and proof-of-concept results.
Assess the feasibility of new technology
For humanoid robots and physical AI, we start with research or a proof of concept. We assess the required actions, accuracy, safety, and operating conditions to determine whether deployment on site is feasible.
Frequently Asked Questions
Can we automate while retaining existing equipment?
We review existing PLCs, sensors and equipment specifications, then connect and automate only the necessary scope. We consider approaches suited to your workplace without assuming complete replacement.
What does a proof of concept assess?
Using real data or equipment, we assess inspection accuracy, cycle times and operational workload. We also identify the conditions for production deployment and remaining issues at this stage.
Can you also handle safety measures and peripheral equipment integration?
Yes. We review personnel movement, stop conditions and signal integration with peripheral equipment, then define the implementation scope across mechanical, electrical and software systems.