Required demand
7,500 samples/month
Capacity & Resource Model
Do we have enough laboratory capacity for what the operation requires?
The Capacity & Resource Model establishes how much sustainable analytical capacity the laboratory actually has, where it is constrained and what resources are required to meet current and future demand.
Client situation
When it is needed
For operations facing rising sample volumes, changing analytical demand, persistent bottlenecks, uncertain staffing requirements, equipment investment decisions or laboratory expansion.
Capacity logic
Installed capacity is not the same as sustainable operating capacity.
Illustrative model — not project performance data
7,500required samples / month
Constraint: Pulverising · 6,500 samples/month
Test scenarios before selecting the lowest-risk configuration.
One operating system
What Sirius examines
- 01Demand
- 02Analytical Route
- 03Process Time
- 04Equipment Capacity
- 05Availability
- 06People
- 07Shifts
- 08Bottlenecks
- 09Turnaround
The purpose is to distinguish installed capacity from sustainable operating capacity. Equipment may appear sufficient on paper while downtime, shared resources, variable routes, staffing or queues prevent the required service.
Evidence base
Typical evidence reviewed
- Sample volumes and demand patterns
- Sample types and analytical routes
- Turnaround requirements
- Equipment capacities and cycle times
- Equipment availability and downtime
- Operating hours and shift patterns
- Staffing by process and competency
- Work-in-progress and queues
- Reruns and reprocessing
- Maintenance requirements
- Planned future volumes
- Proposed equipment or process changes
The work
What Sirius does
- 01
Define the service requirement
Establish normal, peak and future analytical demand.
- 02
Map the analytical routes
Identify the process steps and resources consumed by each sample stream.
- 03
Establish effective capacity
Calculate realistic capacity using actual cycle times, availability, operating hours and constraints.
- 04
Identify bottlenecks
Determine which processes, equipment or resources control overall capacity.
- 05
Test operating scenarios
Evaluate changes in shifts, staffing, equipment, maintenance, workflow or sample allocation.
- 06
Define the required configuration
Show which combination of resources can meet the required service level.
Scenario testing
Where simulation is useful
Where multiple sample streams, shared equipment, variable arrivals, queues, downtime or competing priorities make the system difficult to predict, Sirius can use discrete-event simulation to test how the laboratory behaves over time.
ArrivalsQueueProcessShared resourceQueueAnalysisReport
- What happens during peak demand?
- Where do queues form?
- How much spare capacity exists?
- What happens if equipment goes down?
- Will another shift solve the problem?
- Does new equipment remove the real constraint?
The purpose of simulation is not complexity for its own sake. It is to test decisions before resources are committed.
Decision support
What the client receives
- Current analytical demand
- Sustainable capacity by process
- Critical bottlenecks
- Equipment utilisation
- Workforce requirements
- Shift requirements
- Capacity headroom
- Future demand scenarios
- Options for closing capacity gaps
The model gives management a defensible basis for decisions about people, equipment, shifts, workflow and capital expenditure.
Illustrative only
Example output
ILLUSTRATIVE MODEL — NOT PROJECT PERFORMANCE DATA
Process capacity
Drying — 10,000
Crushing — 9,000
Pulverising — 6,500
Fire Assay — 8,000
ICP — 11,000
Crushing — 9,000
Pulverising — 6,500
Fire Assay — 8,000
ICP — 11,000
System constraint
Pulverising — 6,500 samples/month
Scenario testing
Add equipment — 8,500
Add shift only — 7,200
Improve availability — 7,600
Workflow + maintenance + shift — 8,300
Add shift only — 7,200
Improve availability — 7,600
Workflow + maintenance + shift — 8,300
Management decision
Select the lowest-risk configuration capable of meeting required demand.
Experience behind the work
Relevant evidence
Product routing
When this product leads to another product
Capacity sufficient but performance poorLaboratory Performance Diagnostic
Multiple laboratories need comparisonLaboratory Network & Operating Model
New capability requiredBuild, Transition & Operate
Capacity requires ongoing monitoringAnalytical Performance System
Next step