Solutions
Model Audits
Is Your Simulation Model Fit for Purpose?
Simulation models can influence major decisions involving production capacity, equipment sizing, operating strategies and capital investment. Before relying on their results, it is important to establish whether the models are technically sound and appropriate for their intended application.
MISIM provides independent reviews of existing simulation models, examining their assumptions, data, logic, validation and analytical methods. We assess whether the model represents the operating system with sufficient accuracy and detail to support the decisions being considered.
Whether developed internally or by an external consultant, an independent audit can identify weaknesses, clarify limitations and establish what improvements may be necessary before the model is used for further analysis.
Verify Model Logic and Implementation
A model may produce plausible results while containing errors in its underlying logic, calculations or representation of operating behaviour.
We review model structure, equipment behaviour, material flows, resource interactions and operating rules to identify potential errors, inconsistencies and omissions.
The objective is to establish whether the model has been implemented correctly and behaves as intended.
Assess Assumptions and Validation
A correctly implemented model is not necessarily a credible representation of the operation.
We examine input data, engineering assumptions, reliability parameters, operating conditions and validation evidence. Where appropriate, we compare model behaviour with historical performance, engineering calculations or independent benchmarks.
We also assess whether the model adequately represents variability and uncertainty relevant to the decisions it supports.
Evaluate Results and Decision Readiness
Even a technically sound model may not be appropriate for every application.
We review scenario design, experimental methods, sensitivity analysis and the interpretation of results to determine whether conclusions are supported by the available evidence.
Our findings identify limitations, areas requiring further validation and recommended improvements, helping clients determine whether the model is suitable for its intended decision or requires additional work.
