Capstone 2.0 Business simulation

@Michael7932

Optimizing the shop floor on screen, before you touch the line Missed due dates, hidden bottlenecks, and “perfect” plans that break on day one usually point to one thing: schedules that ignore real-world variability. I’ll build a production-scheduling operations simulation that captures the messiness setup/changeovers, shift calendars, breakdowns, rework, and stochastic process times so you can test policies safely and pick the one that ships. What I’ll deliver (straight to your brief): Comprehensive DES model (AnyLogic/Simio or Python+SimPy) of your routing, resources, queues, and constraints. Realistic schedulers: dispatch rules (SPT/EDD/CR), finite-capacity forward/backward planning, and optional meta-heuristics (GA/tabu) for sequencing. Scenario lab: demand spikes, machine downtime, lot sizes, overtime, run what-ifs before committing. KPIs you care about: makespan, lateness, on-time delivery %, WIP, throughput, utilization, schedule adherence; with sensitivity analysis. Project pack: approach & assumptions, experiment design, data schema (routes, distributions, setup matrix), and a maintenance guide. How this helps: choose the policy that minimizes lateness and WIP, quantify ROI (e.g., overtime vs. due-date penalties), and de-risk go-live with evidence. Portfolio & relevant work are available on request (job-shop and flow-line schedulers, digital-twin pilots).