Predictive Maintenance Expert in Germany

• Strategic and operational leadership of the technical service organization
• Improvement of all processes and workflows
• Development and introduction of a service management IT tool incl. AI database, customer app, and self-service portal

• Building, implementing and selling automated Data Science solutions such as Scorecard Factory and Forecast Factory
• Implementation of automated end-to-end cloud processes
• Development of LLM and NLP models
• Creation of interactive reports
• Support for national and international large corporations as well as medium-sized companies in implementing ML projects

• Own the software system architecture for laboratory automation products; specify interfaces across software, middleware, hardware and motor control in a regulated IVD environment.
• Led architecture evaluations and proof-of-concepts for integrating AI capabilities (anomaly detection, predictive maintenance) into lab automation under medical-device quality standards.
• Introduced GenAI-assisted development tools across the team, improving productivity and code review quality.
• Communicate architecture decisions to product and project management; coordinate research and improvement projects with system, electronics and external partners.

Public sector, regulated environment with legal deadlines and interfaces to justice, finance offices, and authorities. Took over a software product, condition unknown. The handover reported 89 percent completion.

Description / Results:

Review of the current state showed only two months of remaining runtime until year-end. Stabilized the product base in four weeks, including setup. Process logic proven instead of estimated: 181 workflows with 28 steps each verified against the legacy system.

PSA, Peugeot Citroën, France (10/2023 – 05/2024)

• Launch Manager for electrode production rolling lines
• Setup, modernization, and commissioning of cleanroom production equipment
• Management of a team of 15 Chinese technicians
• Recovery of a three-month delay and on-schedule delivery

• Project Management Lead for AI and Modernization implementation (Operations)
• Led the end-to-end RFP process for a predictive maintenance & asset health platform — requirements, evaluation criteria, and vendor selection.
• Negotiated the SOW — scope, timeline, and commercial terms (license split, credits) with the selected vendor.
• Product Owner for the POV pilot — defined scope, KPIs (OEE/downtime), success criteria, and go/no-go milestones.
• Aligned global and site stakeholders across engineering, operations, procurement, and legal — incl. GxP and scalability requirements for multi-site rollout.

Region: EU

• Set up and led an on-site task force to develop the supplier
• Assessed the current on-site quality status
• Reviewed the current results of ongoing actions
• Monitored and supported the implementation of actions arising from customer field complaints
• Provided on-site process training for supplier employees (8-D method, Ishikawa, process documentation)
• Introduced the APQP process, Gemba walks and the LPA audit process
• Optimized the maintenance process, including preventive and predictive maintenance
• Monitored internal VDA 6.3 process audits
• Monitored immediate and corrective actions
• Validated action results
• Managed supplier teams to achieve mission goals: improving process effectiveness, manufacturing process robustness, complaint-handling effectiveness, and proficiency in P-FMEA, 8-D, risk analysis and problem-solving methods
• Ensured effective implementation of actions
• Restored customer satisfaction and confidence in the supplier
• Improved the VDA 6.3 result from C to A (>90 %)

• Engineering & Industry 4.0 / IoT projects with an AI system based on the Robust Design method for products & processes

• Development, implementation & introduction of the AI system Analyser® for Robust Design for products & processes

• AI and Industry 4.0 standard product for preventive and reactive quality and safeguarding as well as maintenance (Predictive Quality and Predictive Maintenance) based on Big & Smart Data

• Working as a freelance ICT journalist for print and online media, as well as a communications consultant for medium-sized German and Dutch IT companies.
• Creating specialist publications, white papers, and journalistic articles on topics such as AI, IT sustainability, climate protection through low-code development, and the introduction of the electronic invoice, etc. (>100 work samples in the original can be viewed at [link])
• Analyzing and reporting on cybersecurity trends, including the NIS-2 directive, Security by Design, and the development of associative computers.
• Conducting expert interviews with specialists and executives on technological innovations such as digital shadows in production and predictive maintenance.
• Numerous publications in trade media such as Wirtschaftsinformatik & Management, IM+io, IT&Production, Digital Business Magazin, eGovernment Computing, etc.

• Consulting as Product Owner, Project Management, SCRUM Master, and Agile Coaching

• Introduced an integrated approach for structural damage detection across concrete, steel, and glass using advanced technologies such as LiDAR and thermal imaging. Highlighted cross-material interactions to enhance diagnostics and enable predictive maintenance.

• Developed an NLP-based medical note simplifier that transforms complex clinical instructions into plain, child-level English. Applied prompt engineering with Flan-T5 transformer models to extract patient-relevant actions and rephrase them into clear to-do items. Built dual Flask and Tornado backends with a printable web interface.

• Lead enterprise architecture, data and AI strategy initiatives across business domains, value streams, SAP, cloud, integration, process intelligence and governance, aligning transformation roadmaps with strategic business outcomes.
• Define enterprise data and knowledge strategy across business domains and enterprise taxonomy, including knowledge graph, data governance with focus on ownership, metadata frameworks, business glossaries, data product orientation, interoperability and AI-enabling architecture.
• Shape AI governance and decision-intelligence strategy using autonomous enterprise concepts, including policies, guardrails, reference architectures and knowledge-based patterns for responsible AI adoption and enterprise knowledge reuse.
• Support SAP S/4HANA cloud migration strategy and evaluate the future SAP ecosystem, including SAP BTP, Integration Suite, Business Data Cloud, SAP Analytics Cloud and Datasphere.
• Drive architecture debt management, portfolio transparency and application rationalization through architecture principles, governance models, decision frameworks and LeanIX-based Enterprise Architecture Management.
• Align business architecture and process intelligence using Signavio to connect value chains, capabilities, processes, data strategy, knowledge flows and transformation roadmaps.
• Define operating models for data governance, architecture governance, cloud, integration, API management, AI governance and knowledge sharing.
• Act as trusted advisor to executive stakeholders and business domain leaders across product, sales, finance, logistics, customer care and shared services.

• Coaching of project participants
• Project management for numerous content migration projects for Telefónica Germany's telecom brands
• Development and reporting of performance metrics
• Promoting collaboration between content managers and UX writers
• Running retrospectives and integrating agile elements
• Team size: 23 people
• Technical environment: Jira, Confluence, Miro, Teams, Adobe Experience Manager, Figma

• Developed and implemented organization-wide discovery framework based on Ulwick’s Outcome-Driven Innovation; enabled 7 Product Owners to systematically identify and quantify unrealized value through shared outcome language and opportunity scoring methodology
• Transformed Product Owner role from backlog clerks to strategic experimenters; established dedicated time budget for autonomous hypothesis testing and discovery activities
• Rebuilt customer journey maps to start at actual user need (tool selection phase) instead of platform entry point; eliminated manual data aggregation work previously done by project teams
• Implemented OKR framework across 4 product teams; defined quarterly objectives with measurable key results (e.g., 40% reduction in manual integration effort, self-service adoption increase)
• Unified 3 separate platform roadmaps through cross-team dependency mapping and shared service agreements
• Supported enterprise sales cycle with ROI modeling and technical due diligence for automotive and defense customers