Field guide
Lot acceptance
Acceptance Sampling: What a Zero-Defect Sample Really Says
A clean sample can come from a defective lot. Check the odds.
Vrolen blog
Ideas for better operational decisions.
Practical field guides for teams connecting operational data, diagnosing system behavior, and choosing what to improve next.
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Field guide
Work design
Standardized-Work Combination Table: A Two-Machine Example
Draw the overlap before adding operator and machine times.
Field guide
Manufacturing data
Manufacturing Lot Traceability Through Splits and Rework
Follow one suspect lot without counting its history twice.
Field guide
Quality risk
FMEA in Manufacturing: A Worked Example and Action Template
A reversed connector, a keyed fixture and an action that stays open until the test is done. Make the risk review useful after the meeting.
Field guide
Pull replenishment
Kanban Calculation: How Many Cards and Containers Do You Need?
Eighteen cards can authorize 360 units. Before adding another card, find out which part of the replenishment loop needs it.
Field guide
Process capability
Cp and Cpk Explained with a Manufacturing Example
The spread can stay the same while Cpk falls from 1.33 to 0.80. A shifted process needs a different response from a noisy one.
Field guide
Statistical process control
Control Charts: When Should You Adjust the Process?
A batch with more rejects deserves context before an adjustment. A control chart gives the investigation a stated rule.
Field guide
Measurement system analysis
Gage R&R: Can You Trust Your Quality Measurements?
A measurement can look precise on screen and still change with the operator. Check the measuring process before judging the production process.
Field guide
Delivery reliability
Calculate OTIF from Customer Receipt Records
The fictional ten-order example starts at 70%. Change a receipt check to see why the joint count matters. Set eligibility and receipt checks from your agreed reporting rules before entering real records.
Field guide
Multi-stage quality
Rolled Throughput Yield: Calculate Quality Across Multiple Steps
Three stages at 90% first-pass yield leave 72.9% of the starting units passing every stage without rework.
Field guide
Production leveling
Heijunka for Mixed-Product Manufacturing: Build a Levelled Schedule
A repeating AABC sequence can match a 2:1:1 product mix. It only works if the line can actually replenish that mix at the planned interval.
Field guide
Manufacturing data integration
OPC UA and MQTT: How Factory Data Reaches Your Analytics
A delivered message can still contain the wrong unit, an old value or a duplicate event. Reliable analytics needs the meaning as well as the connection.
Field guide
Simulation credibility
How to Validate a Manufacturing Simulation Before Trusting Its Results
A model can match weekly output and still miss the daily pattern. Decide what evidence would make its recommendation credible before tuning it.
Field guide
Manufacturing energy performance
Energy per Good Unit: Measure Efficiency Without Hiding Scrap
Electricity can fall 5% while energy per accepted unit rises nearly 7%. The denominator changes the conclusion.
Field guide
Downtime cost
How to Calculate Manufacturing Downtime Cost Without Double Counting
One hour stopped can cost €350, €530 or €1,150 in this worked example. The difference is what happens to the missing production.
Field guide
WIP and lead time
Little’s Law in Manufacturing: Calculate WIP and Lead Time
240 units in progress at 80 units per working hour imply three working hours of average lead time. Here is what that calculation does, and does not, tell you.
Field guide
First-pass yield
First-Pass Yield with Rework: Why 97% Can Hide a 90% Process
970 of 1,000 parts can eventually pass while only 900 pass first time. A clear unit ledger shows the work hidden between those two results.
Field guide
OEE formula
How to Calculate OEE, and What the Number Is Hiding
Calculate OEE from Availability × Performance × Quality with a worked example, then map the score to the six big losses.
Field guide
Takt vs cycle vs lead time
Takt Time, Cycle Time and Lead Time: Three Clocks, Three Different Decisions
Formulas, one worked production example, and the mistakes that lead to bad capacity decisions.
Field guide
Agentic AI
Agentic AI in Manufacturing: From Dashboards to Decisions
What an AI agent is in a plant, three good first use cases, an autonomy ladder and the guardrails that keep it bounded.
Field guide
Downtime Pareto analysis
Your Downtime Pareto Is Only as Good as the Event Model Behind It
Once you have downtime events, how do you decide which one to investigate? Two rankings, a reason hierarchy and one honest caveat.
Field guide
OEE vs throughput
Your OEE Went Up. Customer Output Didn’t. What Happened?
Seven reasons a better OEE score can leave shipments, lead time and delivery unchanged.
Field guide
A3 problem solving
A3 Problem Solving: Use the Page to Structure Thinking, Not Decorate a Project
Seven sections, one worked example and an original worksheet, plus why filling the boxes is not the method.
Field guide
Manufacturing KPI tree
Build a Manufacturing KPI Tree That Explains Performance, Not Just Reports It
A four-level hierarchy that connects business outcomes to the drivers you can actually act on.
Field guide
Line balancing
How to Balance a Production Line Without Just Moving the Bottleneck
A worked example of takt, work content and operator loads, and why the arithmetic minimum is often not achievable.
Field guide
AI root cause analysis
AI Can Accelerate RCA. It Cannot Turn Correlation into Cause.
What AI does well in a root-cause investigation, the four ways it misleads, and how a candidate becomes a verified cause.
Field guide
AI for continuous improvement
AI Should Not Replace Kaizen, It Should Shorten the Learning Loop
A seven-step loop that shows where AI speeds up continuous improvement and what people must still own.
Field guide
OEE vs TEEP vs utilization
OEE, TEEP and Utilization Are Not the Same Thing
Most pages explain the formulas. This one explains which management decision each metric supports.
Field guide
Dynamic bottlenecks
Your Bottleneck Is Not Always the Same Machine
Averages create the illusion of a permanent constraint. Here is how the limiting station moves and how to see it.
Field guide
MTBF vs MTTR vs OEE
MTBF vs MTTR from a Failure Log
Four failures, two time records and a calculation you can check. Learn why the hours behind the average matter as much as the number.
Field guide
Digital twin vs simulation vs process mining
Digital Twin, Simulation and Process Mining Solve Different Manufacturing Questions
A comparison by question and evidence, and a rule for choosing the smallest model that can change the decision.
Field guide
Manufacturing analytics software
How to Evaluate Manufacturing Analytics Software in 2026
Sixteen criteria in four groups, six vendor categories and when each is appropriate. No invented ranking of named vendors.
Field guide
MES vs OEE vs analytics
Do You Need MES, OEE Software, Analytics, or a Continuous Improvement System?
A need-to-layer matrix and a four-layer model: record, execution, analysis and improvement.
Field guide
RCA software
RCA Software Should Preserve Evidence, Not Just Digitize a Fishbone
Five categories of RCA software, the capabilities that matter and how to spot a tool that skips the proof.
Field guide
Continuous improvement in manufacturing
Build continuous improvement into the way your factory operates.
A practical system for finding, testing, verifying, and sustaining manufacturing improvements with evidence.
Field guide
Lean manufacturing
Use lean manufacturing to improve customer flow, not local efficiency.
Understand lean principles, flow, pull, standard work, problem solving, and the conditions required for lasting results.
Field guide
Operational excellence in manufacturing
Turn operational excellence from a slogan into a managed system.
Align purpose, people, processes, technology, and measures so better results survive beyond individual projects.
Field guide
Continuous improvement software
Choose continuous improvement software around the work, not the feature list.
Evaluate CI software for evidence capture, prioritization, experiments, governance, integrations, security, and adoption.
Field guide
Manufacturing software guide
Understand where ERP, MES, MOM, QMS, CMMS, and improvement platforms fit.
Use ISA-95 boundaries and real operating decisions to design a manufacturing software architecture without duplicate systems.
Field guide
The eight wastes of lean manufacturing
The 8 Wastes of Lean Manufacturing, with Examples
Spot defects, waiting, extra movement and the other wastes on a real process walk. Record what you see before deciding what to change.
Field guide
Lean manufacturing vs Six Sigma
Lean Manufacturing vs Six Sigma: Differences and When to Use Each
Compare goals, methods, data needs, strengths, and failure modes before selecting an improvement approach.
Field guide
Continuous improvement project portfolio
Fund the improvement portfolio your operation can actually finish.
Select, sequence, stop, and verify Kaizen and capital projects using system impact, evidence, capacity, risk, and learning.
Field guide
Operational excellence metrics
Measure operational excellence without rewarding local optimization.
Design a connected metric system spanning safety, quality, delivery, flow, cost, people, resilience, and verified improvement.
Field guide
Real-time production monitoring
Turn live production signals into timely, owned decisions.
Connect machines, sensors, orders, quality, and people while controlling latency, context, alarms, security, and response.
Field guide
Value-stream mapping
Move from a static VSM to a testable future state.
Map the flow, add assumptions, and test changes before rollout.
Field guide
Root-cause analysis
Root Cause Analysis: A Worked Manufacturing Example
Follow a recurring packaging fault from the first observation to a testable cause, then use the worksheet for your own investigation.
Field guide
OEE loss analysis
See which OEE loss actually constrains the system.
Connect availability, performance, and quality loss to total flow.
Field guide
Digital twin in manufacturing
Build a manufacturing digital twin that improves decisions, not just visualization.
Connect live operating data to a validated model, test scenarios, and turn results into controlled improvements.
Field guide
Predictive maintenance
Turn machine signals into maintenance decisions the production system can trust.
Use sensors, maintenance history, AI, and simulation to detect degradation and choose the right intervention window.
Field guide
5S methodology
Make 5S a measurable operating system, not a cleanup campaign.
Use sort, set in order, shine, standardize, and sustain to expose abnormal conditions and protect flow.
Field guide
Kaizen event
Run a Kaizen event that produces a verified improvement.
Frame the problem, observe the real process, test countermeasures, and sustain the result after the workshop.
Field guide
Lean Six Sigma
Choose Lean, Six Sigma, or both for the problem in front of you.
Separate flow and waste problems from variation and defect problems, then use evidence to select the right method.
Field guide
PDCA cycle
Turn PDCA into a learning loop, not four boxes on a slide.
Define a prediction, test a controlled change, study the result, and standardize only what the evidence supports.
Field guide
SMED changeover reduction
Reduce changeover time without moving risk into startup.
Separate internal and external setup, simplify adjustments, and verify quality, safety, and total-system flow.
Field guide
Theory of Constraints
Improve the system by managing its current constraint.
Identify, exploit, subordinate, elevate, and repeat while measuring throughput, inventory, and operating impact.
Field guide
Manufacturing bottleneck analysis
Find the bottleneck that actually limits customer output.
Combine cycle time, queues, blocking, starvation, product mix, and simulation instead of relying on utilization alone.
Field guide
Process mining in manufacturing
Turn event logs into an evidence-based view of how work really flows.
Reconstruct process variants from timestamps, compare conformance, and connect discovered delays to physical operations.
Field guide
Industrial AI in manufacturing
Deploy industrial AI around a decision that people can verify.
Connect production data, domain knowledge, machine learning, and simulation with clear confidence and human control.
Field guide
Industrial IoT and smart manufacturing
Connect industrial data without creating a larger blind spot.
Design an IIoT path from sensors and PLCs to interoperable context, secure analytics, and operational action.
Field guide
Manufacturing data analytics
Turn factory data into decisions, not another dashboard.
Build trustworthy manufacturing analytics from PLC, sensor, MES, ERP, quality, maintenance, and manual data, then connect every insight to an operating decision.
Field guide
Production downtime tracking
Track Production Downtime with a Clear Event Log
Record what stopped, when it restarted and what is actually known. Then check how a reporting threshold changes the loss categories.
Field guide
Production scheduling optimization
Build production schedules that survive the real factory.
Combine orders, constraints, changeovers, labor, material, downtime, and uncertainty to test schedules before releasing them to the floor.
Field guide
Predictive quality in manufacturing
Predict quality risk early, without automating bad decisions.
Connect process conditions, product context, inspection results, and machine learning to intervene before defects become scrap or customer escapes.
Field guide
Andon system in manufacturing
Andon System in Manufacturing: How It Works, Examples & KPIs
Use clear abnormality signals, owned escalation, response-time measures, and root-cause follow-up so alerts improve flow instead of becoming background noise.
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