Ideas made useful.
Long-form thinking across industrial engineering, operations research, simulation, optimization, network science, engineering data, software and applied AI. Search or filter the collection by topic.
Network Science for Engineers: Stop Treating Dependencies Like a List
A graph changes the questions we can ask about manufacturing systems, organizations and technical dependencies.
Constraint Thinking: Why Local Efficiency Can Reduce System Performance
The fastest workstation is irrelevant when another resource governs system throughput.
CP-SAT for Manufacturing Scheduling: Decisions, Constraints and Search
Constraint programming is powerful when a schedule is defined less by one equation than by thousands of logical rules.
When Linear Models Are Not Enough: Nonlinear Optimization in Engineering
Many engineering relationships are curved, interacting or discontinuous; pretending otherwise can move the optimum to the wrong place.
Simio vs. SimPy: Choosing a Simulation Environment for Engineering Work
The choice is not visual software versus code; it is about model lifecycle, audience, integration and the questions the model must answer.
Why Coding Agents Change the SimPy vs. Simio Decision
Coding agents reduce the implementation tax of code-first simulation, shifting engineering effort away from GUI mechanics and toward requirements, verification, integration and model credibility.
Little’s Law Is Simple. Using It Well Is Not.
WIP, throughput and cycle time form one of the most useful relationships in operations—but only when boundaries and averages are defined correctly.
Simulation vs. Optimization: Ask Different Questions, Then Combine Them
Optimization searches for decisions; simulation evaluates behavior under uncertainty. Their combination is stronger than either alone.
Knowledge Graphs for Manufacturing: Connecting Work, Resources and Evidence
A knowledge graph is useful when the question crosses tables and the relationships carry as much meaning as the attributes.
AI for Industrial Engineering: Build Tools, Not Chatbot Theater
The highest-value AI applications often sit inside a constrained workflow where context, tools and verification are explicit.
Erlang C vs. Little’s Law: Staffing a Response Queue Without a Discrete-Event Simulation
Two classic queueing tools answer different questions. Together they provide a fast analytical first pass for response-time staffing problems such as inspection callboards.
From Vibe Coding to Engineering: A Practical Kiro Workflow for Coding Agents
Recent lessons from Andrew Ng, DeepLearning.AI, agent-workflow research and hands-on Kiro experimentation point toward the same idea: better agents come from better specifications, context, tools, checks and learning loops—not longer prompts.
SPC Process Stability: Control Limits, Signals and Capability
The equations, assumptions and validation logic behind the Process Stability Lab.
Factorial DOE: Main Effects, Interactions and What the Lab Actually Computes
A transparent 2² experiment from cell means to interaction effects.
Work Measurement, Learning and Forgetting: From Stopwatch Time to Retained Proficiency
Observed time, rating, allowances, takt, staffing and a sequential learn–decay–relearn model.
Factory Flow: Capacity, Variability, Rework and Bottleneck Migration
How the Constraint & Flow Lab turns local rates into a system-level flow argument.
Scheduling: Exact Enumeration, Dispatch Rules and Constraint-Aware Heuristics
What is actually optimal in the Scheduling Lab—and what is deliberately only heuristic.
Analytical Truth: Grain, Cardinality and the Join That Quietly Duplicates Your KPI
Why technically valid SQL can still produce analytically false results.
Reliability Architecture: MTBF, MTTR, Series Systems and Parallel Redundancy
The equations and topology behind the Availability Architecture Lab.
Network Resilience: Centrality, Articulation Points and Structural Failure
How to read the Network Resilience Lab without confusing graph metrics with operational causality.
Queueing & Staffing Lab: Erlang C, Stability and Little’s Law Cross-Checks
A showcase-specific guide to utilization, waiting, service levels and unstable staffing.
Discrete-Event Queueing: Building and Validating the Browser M/M/c Simulation
Poisson arrivals, exponential service, event state and the tests that keep an animation from becoming theater.