Background
An olive processing company needed to understand its true production capacity. The facility was large and complex, with unclear bottlenecks and scheduling challenges that were limiting throughput.
Model Purpose
To develop a detailed simulation model that revealed the dynamics of material flow, identified capacity constraints, and tested various scheduling approaches while quantifying the effects of natural variability in olive processing.
Key model inputs
- Historical production data and processing rates
- Equipment reliability and maintenance schedules
- Harvest variability patterns
- Current scheduling policies and constraints
Key Experiment Factors
- Alternative scheduling approaches including Theory of Constraints methodology
- Capital expenditure scenarios for equipment upgrades
- Impact of harvest variability on throughput
- Buffer sizing and inventory management strategies
System Performance Measures
- Overall throughput and capacity utilization
- Bottleneck identification and quantification
- Capital investment return analysis
- Schedule robustness under variability
Project Results
This decision tool was effective for both capital expenditure decisions and formulation of scheduling policy. The simulation confirmed suspected bottlenecks and revealed that a Theory of Constraints-based scheduling system could significantly improve performance.
15% throughput improvement through scheduling optimization
Capital expenditure decisions validated through simulation before implementation
Better understanding of harvest variability impacts on production planning
Implementation of daily TOC-based scheduling system
Risk-free validation of proposed changes before costly implementation
"The model confirmed bottlenecks at certain operations in the plant... an effective tool to evaluate proposed capital expenditures and scheduling changes over short and long-term periods." - Robert Rugeroni, IT Director
Strategic Assessment
The following list provides links to articles within this document that address strategic assessment issues related to this case study:
- Manufacturing: Capacity Analysis
Ability of current or anticipated capacity to handle projected product mix with validation of capital investment decisions. - Manufacturing: Operational Strategies
Impact of new operational strategies including Theory of Constraints scheduling on throughput and resource utilization. - Supply Chain: Production Capacity
Strategies for dealing with periods of demand over capacity including scheduling optimization approaches.
Documentation
Capacity Planning Simulation of an Olive Processing Plant; M. Michelle Barnes, Richard A. Phelps, Simulation Dynamics; Robert Rugeroni, Lindsay Olive Company.
Press
Virtual Engineering's New Frontier; Kevin T. Higgins, Senior Editor, Food Engineering, 22 March 2003. Andrew J. Siprelle on flow architecture and the "slurp factor"; Robert Rugeroni, MIS director at Bell-Carter Foods, on the pitting and packaging bottlenecks this model found.
Lindsay Olive Company Thrives on Simulation; Food Online case study on the SDI Industry capacity model.