MES Integration & Legacy Modernization

Our methodology for replacing fragmented legacy systems with one integrated production platform.

This case study is a methodology demonstration using an illustrative company. It showcases our approach and capabilities but does not represent an actual client engagement.

European manufacturing company (200-500 employees)ManufacturingCustom Enterprise Software8-14 months (typical)

25-40%

Projected efficiency improvement

Significant

Projected cost savings

50-70%

Projected reduction in manual entry

Minutes

Projected deviation detection

The Challenge

Manufacturing companies often operate with multiple non-integrated systems: an outdated MES, a separate quality registration system, and manual reports for management. Data must be manually retyped between systems, errors are inevitable, and real-time production insight is absent.

Multiple non-integrated legacy systems with manual data transfer
Significant time loss due to manual data entry per production line
Delayed detection of quality deviations
Management reports that are not current

Our Approach

Our methodology provides for a phased migration approach where the new platform is rolled out line by line without production interruptions. Edge computing on the shop floor enables capture of machine data that was previously unreachable.

1

Process Analysis & System Audit

4-6 weeks

Detailed mapping of all production processes, data flows, and integration points with existing systems.

2

Unified Platform Architecture

3-5 weeks

Design of the integrated platform with OPC-UA integration, real-time dashboards, and mobile work orders.

3

Phased Rollout per Production Line

20-30 weeks

Line-by-line implementation with parallel operation to minimize risks and train operators.

4

Optimization & Predictive Analytics

6-10 weeks

Machine learning models for predictive maintenance and production optimization based on historical data.

Projected Outcomes

Based on our methodology, we project elimination of manual data transfer, significant reduction in quality deviation detection time, and real-time production insight for management. Cost savings are primarily expected through efficiency improvement and waste reduction. Exact results depend on the complexity of the production environment and the baseline situation.

Our manufacturing methodology focuses on delivering real-time production insight without production interruptions, through a phased implementation approach that minimizes risks and gradually onboards operators.

Methodology description AppMakelaar Manufacturing Practice

Technologies Used

OPC-UAEdge ComputingReal-time DashboardsReact / Next.jsPythonTimescaleDB

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