Problem Management System with AI Analysis and PDCA Methodology
The Challenge
Lack of a systematic approach to resolving quality issues
An automotive company struggled with recurring quality problems and had no structured system for analyzing and resolving them. Issues were handled ad hoc, without in-depth root cause analysis, leading to their recurrence.
Key challenges:
- No system for registering and categorizing problems
- Issues resolved reactively without root cause analysis
- No PDCA (Plan-Do-Check-Act) methodology in the organization
- Difficulties identifying root causes of problems (Ishikawa, 5Why)
- No tracking of the effectiveness of implemented solutions
- Dispersed knowledge about problems and solutions with no knowledge base
- Ineffective problem-review meetings with no concrete follow-up actions
The Solution Process
Comprehensive problem-solving system with AI and PDCA automation
Implementation of an advanced system for structured problem resolution using PDCA methodology, automated AI analysis (Ishikawa, 5Why), corrective task generation, and a meeting module with transcription and summarization.
System and methodology design
Development of the problem-solving process flow according to PDCA, definition of problem categorization, prioritization, and information flow
3 weeksReporting and categorization implementation
Creation of a problem reporting form, automatic AI-driven categorization, and a prioritization system based on complexity and impact
3 weeksAI Analysis – Ishikawa and 5Why
Implementation of automated AI problem analysis with generation of Ishikawa diagrams, 5Why analysis for each cause, and root cause identification
5 weeksAutomatic task generation
An AI system that automatically proposes corrective and preventive actions based on problem analysis, with assignment of responsible parties and deadlines
3 weeksMeeting system with transcription
Problem-meeting management module with automatic transcription, AI-powered summarization, and generation of action items from meetings
4 weeksKnowledge base and KPIs
Creation of a knowledge base from resolved problems, an effectiveness KPI dashboard, and a solution-stability monitoring system
3 weeksActions Taken
Problem reporting and categorization system
A problem reporting form with automatic AI categorization (quality, processes, safety) and prioritization based on impact and complexity
AI Analysis – Ishikawa and 5Why
Automated AI problem analysis with generation of Ishikawa diagrams (6M), 5Why analysis for each potential cause, and root cause identification
Automatic PDCA task generation
An AI system proposing corrective and preventive actions according to the PDCA cycle, with automatic assignment of responsible parties, deadlines, and completion tracking
Meeting system with transcription and AI
Problem-meeting management module with automatic transcription, AI-powered summarization of key points, and generation of follow-up action items
Knowledge base and effectiveness KPIs
A central repository of resolved problems with the ability to search for similar cases, a KPI dashboard (resolution time, effectiveness, stability), and trend analysis
Results Achieved
Key metrics
Problem analysis time
Solution effectiveness
Recurring problems
Meeting duration
Business benefits
- Structured approach to problems based on PDCA methodology
- Automated AI analysis with Ishikawa diagrams and 5Why
- Reduction of problem analysis time from 4 hours to 30 minutes
- 98% increase in solution effectiveness through root cause analysis
- Automatic generation of corrective and preventive actions by AI
- Meeting system with transcription and automatic summarization
- Knowledge base reducing recurring problems by 68%
- KPI dashboard monitoring solution effectiveness and stability
- Data-driven continuous improvement culture
- 50% reduction in problem-review meeting duration
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