4 Process Level Capacity Analysis

Process Capacity Analysis

1. Overview

  • Focus on analyzing process capacity in various contexts, specifically in relation to admissions processes.

2. Agenda

  • Measures of Capacity: Understand different metrics to quantify and measure capacity.

  • Processing Rate: Learn the rate at which output is processed.

  • Fixed Time Window vs Long Run Averages: Differentiation between immediate capacity and potential capacity.

  • Cycle Time: Distinguish between cycle time and processing time.

  • Performance Metrics: Use flow rate and utilization metrics to evaluate process effectiveness.

    • Flow Rate = MIN[Demand, Capacity].

    • Implied Utilization = Demand / Capacity; Effective Utilization = Flow Rate / Capacity.

  • Process Lead Time: Assess the total time to complete a process including various components.

    • Example: Admissions process analysis using performance metrics.

3. Measures of Capacity

  • Output Measure: Can be expressed as gross output (number of items produced) or rate (items produced per time frame).

  • Fixed vs. Long Run Averages: When measuring capacity, fixed time windows provide immediate capacity, while long-run averages show potential efficiency.

    • Example: Restaurant capacity under both measures.

  • Definitions of Capacity:

    • Processing Rate: Capacity = 1 / Processing Time.

    • Batch Processing: Capacity = Batch Size / Processing Time.

    • Independent Resources: Capacity = (No. of Resources x Batch Size) / Processing Time.

4. Cycle Time Analysis

  • Cycle Time Formula: Average Process Cycle Time = 1 / Flow Rate (where Flow Rate = MIN[Demand, Capacity]).

  • Cycle time helps determine intervals between process repetitions and assesses design efficiency against target capacity.

  • Impact of Capacity on Cycle Time: Generally, higher capacity leads to shorter cycle times, critical in manufacturing considerations like car production targets.

5. Processing in a Batch

  • Batch Processing Evaluation:

    • Total processing time = Fixed Time + Batch Size x Variable Time Per Unit.

    • Defines efficiency in batch contexts, calculating average cycle and processing times.

6. Impact of Batch Size on Performance Metrics

  • Graphs depict the relationship between restaurant capacity and batch size, and cycle time versus batch size.

  • Economies of Scale vs. Diminishing Returns: Increased batch sizes can lead to diminishing returns; optimizing batch sizes is essential.

7. Product or Customer Mix

  • When processing multiple product types, both fixed and variable times must be taken into consideration to ascertain total processing time accurately.

  • Calculate capacity derived from mixed product flows.

8. Application: Admissions Department Analysis

  • Results from Data Entry Steps:

    • Different steps exhibit varying capacities based on personnel and process design considerations.

    • Calculated processing times and throughput for the admissions department, including metrics for utilization at each step.

9. Process Performance Measures

  • Performance Metrics: Focus on flow rate and utilization connections.

  • Implied vs. Effective Utilization Comparison: Effective utilization relates to how many applications can realistically be processed, influenced by bottlenecks.

10. Process Lead Time

  • Defined as the time taken to process a completely through job, order, or customer, excluding waiting times, essential for assessing responsiveness.

  • Breakdown of processing times for both domestic and international applications.

11. Work-in-Process and Little's Law

  • Work-in-Process (WIP): Current number of jobs or orders within a system.

  • Little's Law: Used to estimate one of the three main measures (Flow Rate, WIP, Lead Time) if the other two are known.

    • Formulation: Avg. WIP = Avg. Flow Rate x Avg. Lead Time.

    • Specific application to the admissions department with given metrics, showing calculated averages.