Capacity planning is the process of checking whether a factory has enough resources to meet production demand. These resources can include machines, manpower, tools, space, shifts and working time.
A factory may have orders, but orders alone do not create output. Output depends on available capacity. If capacity is not calculated properly, delivery commitments become risky.
Simple capacity formula
At a basic level, production capacity depends on available time divided by cycle time. For example, if one machine is available for 450 minutes per shift and one part takes 3 minutes, the theoretical capacity is 150 parts per shift.
Why actual capacity is different
Theoretical capacity is not always actual capacity. Breaks, changeovers, breakdowns, rework, waiting time, absenteeism and quality issues reduce actual output. That is why factories should use realistic capacity assumptions.
Machine capacity and manpower capacity
Some operations are machine-constrained. Some are manpower-constrained. Some require both. If the machine is available but the operator is not available, production will still fail. If manpower is available but the machine is overloaded, the plan will still fail.
Bottleneck analysis
The bottleneck is the resource that limits output. A product may pass through cutting, machining, assembly and inspection. If machining has the lowest capacity, it controls the total output. Improving non-bottleneck areas may not improve final delivery.
Factory example
Assume assembly can produce 1,000 units per day, inspection can check 900 units per day and packing can pack 1,200 units per day. The factory cannot ship 1,200 units unless inspection capacity is improved. The real capacity is controlled by inspection.
How Factovare supports capacity planning
Factovare helps connect product data, cycle time, manpower, resource requirement and production planning. This helps factories move from rough assumptions to data-based capacity decisions.
Conclusion
Capacity planning is one of the most important manufacturing decisions. It helps factories understand what is possible before committing to customers. Good capacity planning reduces delivery failure, overtime pressure and daily firefighting.