Lean Digitalization for Manufacturing Operations
Turn equipment data into shop-floor evidence for lean improvement
Orpaon Intelligence connects real production processes through equipment connectivity and supports plan execution, efficiency analysis, quality control, and energy management with six products, so problems have data, measures have verification, and experience can be reused.
Six Products Working Together
MES, OEE, quality traceability, shop-floor error proofing, SPC, and energy management work together around the same production environment.
Website in Ten Languages
The website presents products, solutions, and implementation methods in ten languages for teams across regions.
Single-Line Pilot
Validate data, workflows, and usage on one line or process section before deciding whether to expand.
Multi-System Interfaces
Inventory interfaces among equipment, ERP, WMS, QMS, and metering systems according to site conditions and define data boundaries.
Typical challenges
Typical challenges
Waiting Losses
Material shortages, inspection waits, production-change handoffs, and delayed task assignment are easily recorded as generic stoppages, obscuring where waiting actually occurs.
Downtime Losses
When short stops and fault causes rely on after-the-fact entry, downtime frequency, duration, and accountability boundaries become distorted.
Quality Losses
Defects found only at final inspection, or defects that cannot be linked to equipment, batches, and process parameters, increase rework and investigation costs.
Material Losses
Inconsistent feeding, returns, work in process, and batch status can lead to incorrect use, excess inventory, or discrepancies between records and physical stock.
Data Losses
Paper records, isolated spreadsheets, and duplicate entry delay data and make it difficult to turn team experience into reusable standards.
Energy Losses
Without submetering, energy used during idling, standby, and non-production periods cannot readily be linked to specific improvement actions.
Products
Six products with distinct roles in the improvement loop
MES manages work-order execution and shop-floor reporting, OEE breaks down availability and performance losses, and quality traceability links batches and process records. Shop-floor error proofing validates critical actions before execution, SPC observes process variation, and energy management links consumption to equipment and production states.
Factory Energy Management and Energy Analysis
Break down utility bills by area, system, equipment, and product to build an explainable energy baseline
Batching and Feeding Error Proofing with Lot Traceability
Turn recipe requirements into executable checks, weighing steps, and batch records on the shop floor
Production-Line MES and Quality Traceability
Ground work-order execution in evidence, record process exceptions, and make product genealogy traceable
OEE and Andon Visualization
Go beyond a single metric by breaking losses into actionable causes and accountability loops
Machine Data Acquisition and Production-Line Connectivity
Capture data from mixed-vendor equipment accurately and reliably before reusing it for monitoring, traceability, and analysis
SPC Statistical Process Control
Move from final pass/fail decisions to process-stability monitoring and capability evidence
Data and system architecture
Capture equipment data accurately before analyzing efficiency
Equipment connectivity is not simply sending signals to a database. Running, idle, fault, output, alarm, and process-parameter data must be aligned in time and associated with work orders, products, shifts, and stations to explain what happened on the shop floor.
For legacy equipment that cannot be connected directly, assess combinations of controllers, sensors, and manual supplemental entry, defining the respective boundaries of automatic acquisition and manual records.
- 1Standardize foundational codes for equipment, lines, work orders, and products
- 2Record data sources, acquisition intervals, and exception-handling rules
- 3Retain the rationale for conversions between raw signals and business states
Implementation
Diagnose
Walk the shop floor around bottlenecks, downtime, quality, or traceability problems, defining what needs validation before accumulating features.
Pilot
Select a line with clear boundaries and confirm the pilot scope, foundational data, user roles, and acceptance definitions.
Connect
Inventory controllers, instruments, and existing systems; acquire states, alarms, output, and necessary process data; and retain semantic documentation.
Close the Loop
Connect exception detection, accountable handling, outcome confirmation, and review, testing measures with like-for-like before-and-after data.
Standardize
Formalize data dictionaries, exception classifications, operating procedures, and access rules to reduce inconsistencies between teams.
Replicate
Adapt templates to equipment differences and process conditions before expanding to other lines, with ongoing maintenance and problem-feedback mechanisms.
Industries
Automotive Components & Tires
Connect machine-fleet process data, product identities, and group-level collaboration into a verifiable traceability chain
Food Manufacturing
Bring recipe execution, batch evidence, and production-line losses into one shop-floor closed loop
Home Appliance & Equipment Manufacturing
Bring multi-brand legacy equipment into one production-coordination and continuous-improvement loop
Materials & Chemicals
Turn high-volume process signals into clear screens, prioritized alarms, and traceable events
Cases
Large-Scale SCADA and Alarm Management for a Chemical Plant
To address dense process signals and complex coordination between screens and alarms in a continuous chemical plant, the project implemented large-scale SCADA and established a unified mechanism for alarm prioritization, acknowledgment and reset, event archiving, and ongoing management, helping operating roles identify events requiring response amid high signal volumes.
Coordinated OEE, Batching Error-Proofing, and Weighing Traceability in Food Manufacturing
To address manual-batching risks, opaque production-line losses, and fragmented batch data, the project implemented an OEE model line and expanded it to a two-plant platform. The scope also covered Andon, manual batching error-proofing, chocolate-piping monitoring, weighing traceability, alarm publishing, energy management, and annual maintenance.
Phased Digital Upgrades for Multi-Brand Home Appliance Production Lines
To address heterogeneous legacy-line equipment, limited status visibility, and legacy-line upgrade constraints, the project was implemented in phases: LED displays and Andon, OPC connectivity, PCM/SUS line monitoring, #3 PCM line-wide MES, motor assembly and testing, and subsequent server upgrades and annual maintenance.
Insights
5S Layered Audits: Move from Scoring Inspections to Sustaining Standards and Solving Problems
The direct answer for a 5S layered audit is to establish area-specific standards for Sort, Set in Order, Shine, Standardize and Sustain, have different management levels inspect according to their distinct responsibilities, and route every finding through ownership, correction, verification and standard updates. The goal is not to maximize scores, but to expose abnormalities more readily and sustain basic working conditions. The audit checklist is only the vehicle; the closed loop on the shop floor is what matters.
Andon Response Loop: From Abnormality Calls to Review and Improvement
The direct answer for an Andon response loop is to give every abnormality a clear type, owner, status and escalation path, then complete discovery, calling, acknowledgment, arrival, treatment, recovery, closure and review in sequence. Lights and dashboards are only information entry points. Andon effectiveness depends on clear response ownership, consistent timing definitions, and whether abnormalities become evidence for sustained improvement.
Manual Batching Error-proofing Guide: From Scan Prompts to a Closed Weighing Loop
The direct answer for manual batching error-proofing is to combine recipe version, material identity, addition sequence, live weight, tolerance and exception authorization into an execution chain that cannot be skipped at will. Scanning answers ‘Is this the right material?’ Weighing comparison answers ‘Is the quantity within the allowed range?’ Lot linkage answers ‘Can the event be traced afterward?’ All three must be designed together with material issue and return, lot changeover and exception handling. On-screen prompts alone cannot justify a claim that errors have been eliminated.
Frequently asked questions
Can legacy equipment without standard communication interfaces be included in a pilot?
Start with an equipment and controller inventory, then assess existing interfaces, added sensors, edge acquisition, or necessary manual supplemental entry. Whether automatic acquisition is possible and which signals are available must be based on on-site verification.
Do we still need MES if we already have ERP?
It depends on the shop-floor gap. ERP typically coordinates orders, materials, and finance, while MES focuses on work-order execution, production reporting, work in process, and process data. The project first allocates system responsibilities before deciding whether MES is needed and how to integrate it.
Will an OEE dashboard alone solve downtime problems?
No. A dashboard only presents results calculated under defined rules. Accurate downtime causes, exception-handling workflows, and review mechanisms are also required. Unclear data definitions can allow an OEE figure to conceal problems.
Why start with a single-line pilot?
A single-line scope makes it easier to validate acquisition stability, state definitions, role operations, and exception loops while exposing equipment differences and foundational-data issues early, reducing rework from a large-scale one-step rollout.
What information should we prepare for the initial discussion?
Prepare line and process flows, a list of major equipment and controllers, current pain points, existing systems, and the problem you want to validate first. If complete information is unavailable, we can begin with shop-floor interviews and an inventory.
Choose one line and define the problem and data boundaries
Tell us about your process, equipment, and the problem most in need of validation, and we can determine an appropriate pilot scope together.