Francois Van Huysteen

Francois has over thirty years of experience in discrete event simulation, providing consulting, training, and technical support services. He helps organizations gain deeper insight into their operations by developing simulation models that accurately represent business processes and eliminate uncertainty in decision-making. Through rigorous analysis of key performance drivers, he delivers data-driven insights that support sound strategic and operational decisions.

He has led successful projects across South Africa, West Africa, the United States, and the Middle East, covering warehouse and supply chain logistics, manufacturing, facility planning, mining logistics, airline passenger transportation, and business process analysis.

His clients include SASOL, Emirates Airline, Saudi Aramco, Anglo American, Harmony Gold Mining Company, Petra Diamonds, Standard Bank, Capitec Bank, Promasidor (Nigeria), Ceres Fruit Processors, and Pella Corporation (USA).

In addition to consulting, Francois lectured simulation part-time to Industrial Engineering students and served as an external examiner at several South African universities. He has also presented simulation workshops and conference talks throughout his career.

• Practical Reliability Engineering - Patrick D.T. O’Connor (UK)(1990)
• Applied Maintainability, Availability and Operational Readiness Engineering - Dr Dimitri Kececioglu (USA)(1990)
• ARENA Simulation Course -1994
• Business Re-engineering Course: Software tools and Concepts - 1994
• Crossing the Chasm: How to market high technology products - 1995
• Negotiation Skills - Dennis Lewis (2000)
• Simio Training Course – Dr C Dennis Pegden (2009, Pittsburgh, PA, USA)
• Business Coaching – Niel Malan (2017)
• AnyLogic Training Course - Clemens Dempers (2025)

• Simulation: Change Decision Making in Mining Logistics – Crushing & Grinding in Mining Expo & Conference – 2011 – Johannesburg, South Africa
• Simulation provides insight needed to balance warehouse In & Outbound Demand – Winter Simulation Conference 2014 – Savannah, GA, USA

Determine the number of required briefing/debriefing rooms in new operations building to ensure timeous movement of crew by using a simulation model representing crew movement and constraints.

(Capacity Planning - Middle East Airline)

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Investigating alternative transportation policies from plant to customer for a big window and door manufacturer in the USA. Point out unexpected cost drivers with simulation model to save money.

(Supply Chain Logistics - USA Manufacturer)

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Build simulation model for petroleum company to assist in ways to reduce time in plant for trucks, determine loading/offloading bays required and determine safety levels of product storage tanks.

(Logistics - Middle East Oil & Gas Company)

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Simulate outbound logistics for GTL plant. Investigate loading from final product tanks into road and rail tankers to determine sufficient tank sizes, required number of road and rail tankers and required number of rail loading bays.

(Supply Chain - Canadian Oil & Gas Company)

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Model steady state production for block cave and sub-level cave to determine LHD fleet size and if planned throughput could be achieved. Simulation model is used by mine for ongoing planning.

Capacity Planning - SA Diamond Mine)

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Simulate in- and outbound warehouse operations to determine reason for bottleneck and solution required to balance in- and outgoing demand.

(Warehouse - SA FMCG Company)

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Simulate underground mine workshop to determine number of work bays required. Prove that 79% productivity loss due to waiting time could be prevented by adding a repair bay.

(Capacity Planning - Southern African Diamond Mine)

Discrete Event Simulation (DES) is a specialized capability typically provided by simulation subject matter experts (SMEs).

Organizations frequently face strategic and tactical decisions that ultimately have financial implications. When evaluating such decisions, they often engage simulation SMEs to develop a model of the relevant business processes. This model represents the specific part of the organization under investigation—such as assessing the impact of a factory expansion on throughput, or a new marketing campaign on resource allocation.

Usually starting at the current (As-Is) scenario, the simulation model is then used to explore multiple “what-if” (To-Be) scenarios, effectively enabling the organization to test potential future outcomes in a risk-free environment. The objective is to provide senior management with robust, scientifically grounded decision-support insights.

To deliver these insights, simulation SMEs must carefully interpret and analyze the results generated by the model. This requires rigorous and often extensive data analysis to ensure that conclusions are accurate, meaningful, and actionable. E.g. queue lengths, time spent in queues and resource (constraint) utilization are considered to identify bottlenecks.

Discrete event simulation is particularly effective for:

· Greenfield Projects: Model new facilities, processes, or systems

· Brownfield Analysis: Analyze modifications to existing operations

· Variability Management: Understand and mitigate the impact of variability

· Resource Optimization: Optimize resource allocation and system configurations

· Performance Enhancement: Improve overall system performance and efficiency