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Automotive Manufacturing Focus
SECTION 1 OF 5 — DOWNTIME & OEE
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Section 01 · Downtime & OEE
Production Visibility
How well does your team detect, measure, and respond to production losses?
Q1 How quickly does your team typically identify the root cause of an unplanned downtime event?
Same shift — we have real-time alerts and structured response protocols
Within 24 hours — we investigate during the next day's review
2–5 days — analysis is done manually when time allows
We often don't find the true root cause — we patch and move on
Q2 How is your OEE (Overall Equipment Effectiveness) currently tracked?
Automated system — live dashboard updated in real time
Semi-automated — pulled from our MES/ERP daily or weekly
Manual spreadsheets — supervisors enter data each shift
We don't formally track OEE
Q3 Roughly how many hours of unplanned downtime does your plant experience per week (across all lines)?
Less than 2 hours — we have strong PM and response programs
2–5 hours — it's manageable but still costly
5–15 hours — it's a consistent problem we haven't solved
15+ hours — downtime is one of our biggest operational challenges
Section 02 · Continuous Improvement Programs
Kaizen & DMAIC Execution
How effectively do your CI initiatives launch, run, and deliver lasting results?
Q4 How would you describe the current state of your Kaizen / CI program?
Active and structured — we have a formal pipeline with tracked ROI
Reactive — we run events when problems surface, not proactively
Inconsistent — initiatives start but rarely sustain past 90 days
Minimal or non-existent — CI is not a structured program here
Q5 When a DMAIC or structured improvement project is launched, how is progress tracked?
Dedicated project management system with milestone tracking
Spreadsheets or shared drives — managed by a CI team member
Meeting notes and informal check-ins — no central tracking
Projects aren't formally tracked after kickoff
Q6 How many dedicated Continuous Improvement staff (CI Managers, Lean Engineers, OpEx roles) does your plant currently have?
3 or more full-time CI professionals
1–2 dedicated CI staff members
CI is a part-time responsibility for someone in another role
No dedicated CI staff — it falls to plant managers and supervisors
Section 03 · Data & Reporting
Operational Intelligence
How is production data captured, reported, and used to make decisions?
Q7 How are daily/weekly KPI reports produced and distributed to plant leadership?
Automated dashboards — leadership has live access anytime
Semi-automated — scheduled reports pulled from our systems
Manual — a staff member compiles data each morning/week
Informal — shared in meetings with no standardized format
Q8 When a quality issue (scrap spike, rework increase) is detected, how quickly do department managers receive the alert?
In real time — automated alert system notifies the right people instantly
Same shift — supervisor catches it during a walkthrough or end-of-shift review
Next day — when daily production numbers are reviewed
End of week — during the weekly quality or operations review
Q9 Which of the following best describes your current scrap and rework situation?
Under control — tracked daily, trending in the right direction
Stable but above target — we know the number but haven't solved it
Variable — some lines are okay, others are consistently problematic
A significant ongoing cost — scrap/rework is one of our top 3 operational issues
Section 04 · AI & Technology Readiness
Digital Maturity
Where does your facility stand on the Industry 4.0 adoption curve?
Q10 Which of these systems does your plant currently use? (Select the best match)
Multiple integrated systems (ERP + MES + Quality + OEE platform)
2–3 systems — they work but don't share data well
Primarily one main system (SAP or similar) plus spreadsheets
Mostly manual — spreadsheets and paper-based tracking dominate
Q11 How would you rate your leadership's current appetite for AI and smart manufacturing investment?
High — it's a strategic priority and we have budget allocated
Growing — leadership is interested but wants to see proof of ROI first
Mixed — some champions internally but no formal initiative yet
Low — focus is on core operations, technology investment is on the backburner
Q12 Has your plant previously attempted to implement any AI, machine learning, or advanced analytics tools?
Yes — successfully deployed and actively using
Yes — piloted but it didn't stick / wasn't the right fit
No — we've explored it but haven't committed to anything
No — this would be our first AI initiative
Section 05 · Your Details
Where to send your report
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PLANTPILOT AI IS ANALYZING YOUR RESPONSES
Calculating AI Readiness Score…
Identifying highest-impact opportunity areas…
Estimating annual cost of current gaps…
Generating your personalized recommendations…
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out of 100
Calculating…
Estimated Annual Cost of Current Gaps
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Annual downtime cost (est. from your responses)
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Scrap / rework cost exposure (industry benchmark)
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CI program inefficiency (delayed decisions × volume)
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