Fundamentals of Capacity Planning and Analysis

Explore forward-looking capacity planning and analysis with bottleneck and theory of constraints insights, capacity verification, and queuing models to optimize throughput, utilization, and wait lines.

Explore capacity planning by distinguishing input and output capacity, using cycle times, with injection molding, roller coasters, and university processes to improve the maximum rate of transforming inputs into outputs.

Explore how design capacity, effective capacity, and planned capacity cushion define a production process's true output within constraints, illustrated by a plastic spoon molding example and real-world bottlenecks.

Practice exercise to calculate design capacity, effective capacity, and planned capacity cushion. For Mighty Foods' two canning machines, use the Excel file to compute annual cans with two shifts.

Explore capacity metrics from design to demonstrated capacity, analyzing utilization and efficiency, and identifying unplanned losses like absenteeism and lack of raw material to drive corrective actions.

Identify and manage bottlenecks in multi-step manufacturing by applying theory of constraints to balance throughput, using actual capacity data for spoons, forks, knives, napkins, and packaging.

Learn how a bottleneck analysis model in Excel simulates capacity across injection molding, napkin folding, packaging, and shipping, highlighting utilization, inventory buildup, and throughput under different scenarios.

Identify the process constraint, exploit it with short-term fixes, subordinate all others, evaluate and widen the bottleneck, then remove it and re-evaluate for continuous improvement.

Explore bottleneck analysis using a five-step process, identify inventory patterns ahead of bottlenecks, and test improvements via the constraint exploitation and flow balancing in a hands-on spreadsheet.

Identify how capacity planning sets the aggregate, long-term capacity to meet customer demand by grouping similar parts, estimating required machines, and embracing approximation rather than scheduling.

Use the single part aggregation capacity planning formula to connect machine capacity, annual demand, per-piece time, and available hours with a capacity cushion; see a thousand-piece example in Excel.

Use single part aggregation in a spreadsheet to calculate the required machines from demand and cycle times, applying a 15% capacity cushion and rounding options.

Explore capacity planning with multiple part aggregations and part families, incorporating demand, processing time, setup time per lot, and production lot size to calculate machines under a capacity cushion.

Explore modeling multiple part aggregations for product families using annual demand, processing time per unit, and setups to estimate the total machines required and capacity cushion.

Explore three capacity change strategies: expansionist, Simon says, and wait-and-see, and compare capacity leads demand, incremental adjustments, and capacity follows demand, with seasonal and flexible-workforce examples.

Learn the wait and see capacity strategy, where capacity follows demand to reduce capital risk, and review short, medium, and long term changes like overtime, outsourcing, and flexible work cells.

Explore overall equipment effectiveness (oee) as a capacity planning metric in manufacturing, breaking it into availability, performance, and quality, and examining the six big losses.

Define a well defined, consistent metric for your operation, such as oe, to enable month over month and internal comparisons. Document what counts and what doesn't to ensure clarity.

Understand capacity verification through run at rate audits, where a 4–8 hour production run documents runtime, downtime, cycle time, and defects to estimate annual capacity.

Learn to build and apply an Excel-based capacity verification model with run rate audits across multiple operations, identify bottlenecks, and compare utilization to tack time.

Explore wait line models and queueing models used in capacity planning for customer service, highlighting how wait time drives satisfaction and how total cost guides optimal service investment.

Analyze wait line model designs in service systems, focusing on how wait lines, servers (channels), and service phases shape performance across single- and multi-server configurations.

Explore the mathematics of wait line models by examining lambda and mu, Poisson arrivals, and exponential service times, with practical Excel tools to analyze utilization, Lq, and Wq.

Model a simple wait-line in excel using lambda, mu, and utilization to compute Lq and Wq, and use goal seek to keep the average in line at three or fewer.

Explore a multi-server wait-line model in Excel, using inputs like lambda, service rate, and units to compute utilization, queue length, time in the system, and related probabilities.

Conclude the course by highlighting tools, data models, and capacity analysis approaches in manufacturing, with access to resources like Excel spreadsheets and cheat sheets, and Udemy support within 48 hours.

Explore capacity planning and analysis through analytics, including supply chain analytics, PAP, and foundations in statistical decision making, with practical case studies, downloads, and Excel Solver applications.