Case Studies

Six industrial engagements, a measured result every time

Every engagement is presented through the same lens: the client's challenge, our approach, the solution deployed, and the impact observed. The figures quoted are those measured by the companies concerned.

Leading multi-domain risk analysis on an A330 final assembly line

Challenge

On a final assembly line covering the Cabin, Green, Electrical and other production areas, PFMEA risk analyses were conducted inconsistently from one area to the next. Production validation points (PPVs) remained blocked for want of complete or existing PFMEAs, with a direct effect on production milestones. The preliminary risk assessment process was, in addition, still handled manually.

Approach

Leading PFMEA activities across all areas of the A330 FAL, with process analysis and risk assessments covering process, quality, safety and HSE dimensions. Facilitating cross-functional workshops bringing together Production, Quality, HSE, MEPE, Industrialization and Engineering teams, to confront each function's view on every failure mode and reach a shared risk rating.

Solution

Defining, coordinating and monitoring action plans to mitigate the risks identified and strengthen process robustness. Transversal leadership and support to PFMEA facilitators across the organization, complemented by PFMEA methodology training and coaching sessions delivered to multidisciplinary teams in accordance with Airbus standards. Monitoring and reporting on PPVs blocked by missing or incomplete PFMEAs, coordinating the relevant teams to secure production milestones.

Digital enablement

To support this operational work: collecting, cleaning and analysing PFMEA-related data to inform decision-making and continuous improvement. Designing KPI dashboards in Looker Studio, and developing web applications (Google Apps Script, HTML, CSS, JavaScript) to streamline the Preliminary Risk Assessment process. MEPE teams were trained and supported in the effective use of these tools.

Impact

  • PFMEA methodology harmonized and rolled out across all domains of the line, in line with Airbus standards.
  • Process robustness strengthened through risk mitigation action plans defined and tracked over time.
  • Blocked PPVs tracked and released through coordinated cross-functional action, securing production milestones.
  • Teams and PFMEA facilitators upskilled, making the approach self-sustaining.
  • Risk management process automated, improving efficiency, visibility and data-driven decision-making.
PFMEARisk AssessmentQualitySafety & HSEWorkshop FacilitationTraining & CoachingLooker StudioGoogle Apps Script

Steering two $20M production lines with data

Challenge

Performance steering across two production lines relied on manual data pulls. Warehouse stockouts were discovered too late to be anticipated, and the gaps between MES time logs and SAP standard times had never been analysed.

Approach

Operating as production manager for the area — two lines, incoming warehouse inspection, more than twenty operators, technicians and CNC machinists — defining the genuinely useful indicators with the teams, then building the steering tools directly.

Solution

Three Power BI dashboards that structure the area's steering today: line performance (OLE, direct and indirect time from the MES, cycle time against SAP standards), real-time warehouse stock broken down by bill of materials, and incoming inspection tracking. The stock dashboard has become the backbone of the weekly meeting that feeds the monthly production plan.

Impact

  • $20M in annual revenue steered on real-time data.
  • Urgencies anticipated toward purchasing and supply chain rather than absorbed.
  • Operators upskilled into technician roles — CNC programming, Kuka robotics.
Power BISAPMESLeanSQCDPTeam Leadership

Reducing scrap through quality performance management

Challenge

At an equipment production site for the oil industry, in the middle of an SAP and MES rollout, non-conformities were tracked but not steered. Quality data was incomplete, there was no visibility on closure rates, and the root causes identified were never put to use.

Approach

Starting from data quality itself: cleaning and structuring quality management data inside SAP. In parallel, conducting root cause analyses, running PFMEA and facilitating action plans with the production and quality teams.

Solution

A Power BI dashboard connected to SAP HANA, built in DAX and Power Query, surfacing closure and data-cleanliness indicators by line and by open task, alongside Pareto analyses by defect, by cause and by product.

Impact

  • 27% scrap reduction measured over the 2023 financial year.
  • Ranked in the worldwide top 3 of SLB's DIGUP programme.
  • Presented to executive leadership — VP Delivery Reservoir Performance and VP Manufacturing.
SAP HANAPower BIDAXPower QueryPFMEARoot Cause Analysis

Digitalizing maintenance and asset traceability

Challenge

First-level maintenance was managed on paper with no real-time tracking. In parallel, a 600 to 900 m² rework yard had no traceability at all: locating a single forklift required several minutes of physical searching.

Approach

Design carried from user experience through to deployment, working directly with the operators who would use the tools on the floor, tablet in hand.

Solution

Two business applications. The first dedicated to maintenance: per-station instruction sheets, photo-based checklists and a real-time tracking dashboard. The second dedicated to the rework yard: locating each forklift by serial number or work order, in and out dates, consolidated rework time for the manager, and tablet access for operators.

Impact

  • Maintenance tracked and steerable, where it had been invisible on paper.
  • Instant forklift location from a tablet, replacing minutes of physical searching.
  • Rework time indicator available for the first time, opening the door to optimizing it.
Power AppsSharePoint ListUX / UITPM

Securing an ERP migration through master data reliability

Challenge

Ahead of a transition to a new SAP version, production module data was inconsistent: obsolete routings, poorly defined operations, incoherent component assignments and unqualified logistics flows. Migrating as-is would have carried the disorder into the new system.

Approach

Joining the migration task force with full responsibility for configuring and cleaning the production module across the assigned scope. In parallel, acting as industrialization lead on customized products.

Solution

Creating and reworking routings and operations, assigning components workstation by workstation, and defining the logistics flow — kanban or kit — for every part. On the industrialization side: validating the manufacturability of customized forklifts, reviewing engineering files, validating drawings, supporting operators on the first prototype and acting as the permanent interface with the design office.

Impact

  • Complete data cleanup of the Matrix line, the scope under my responsibility.
  • Migration secured, with no defective data carried into the new system.
  • Logistics flows qualified part by part, the basis for reliable line-side supply.
SAP PPRoutingsBills of MaterialsLogistics FlowsIndustrialization

Making real lead time visible across production loops

Challenge

On a kanban-driven production line, every scan generated a timestamped SAP record forming production loops. Yet the real lead time per work order remained unusable: the data existed inside SAP, but no one was able to read it.

Approach

Modelling the production loops from the SAP records — date, start and end activity — to reconstruct the real path of each work order and derive a usable lead time from it.

Solution

A Tableau dashboard connected to SAP surfacing lead time in real time per work order, accompanied by staff training. In parallel, a standalone VBA solution working from SAP record extracts, built for users without a Tableau licence.

Impact

  • Lead time visible in real time per production loop and per part.
  • Two access channels by user profile, leaving no team without visibility.
  • Existing SAP data finally exploited, with no investment in a new system.
TableauSAPVBAKanbanUser Training

Facing a comparable challenge in your operations?

Each of these engagements began with a thirty-minute conversation about a concrete problem.