3 reasons to follow our course at Tailings Mine Waste 16

I can think of at least 3 reasons to follow our course at Tailings Mine Waste 16 (TMW2016):

a)“Bring Your Own” approach. If you “present a case (make it anonymous to respect confidentiality)”, we will discuss it and propose a road-map to solve the Risk Assessment in the most efficient way (subject to time availability, number of requests, suitability). You will be tapping into more than 20 years of quantitative risk assessment experience on dams, but also on tailings systems ancillary components like pipelines, access roads, power lines and monitoring systems.

b) by the end of the course you will know what results you should get when you perform a risk assessment. How to reliably detect weaknesses that will leave you unwillingly exposed, how much better you will be able to sail through uncertainties if your Risk Assessment is properly made following Optimum Risk Estimates (ORE, ©Riskope) principles.

c) You will learn how a convergent hazard and risk register can be linked to modern remote data acquisition systems (drones), to “business intelligence” type of software storing monitoring results and business data. Your will learn how to integrate Risk Management into extant (or future) Tailings Stewardship programs maximizing efficiency and delineating sustainable mitigative roadmaps.

3 reasons to follow our course at Tailings Mine Waste 16

• “Bring Your Own” approach
• reliably detect weaknesses and recognize uncertainties and finally
• jump into the future: drones, business intelligence, big data

These three reasons would certainly be enough. However, we will also talk about risk tolerance, risk communication, recent accidents and modern solutions.

Have a look at “20 Rules for good Risk Assessments”. If your risk assessments do not cover all the points described in that paper then you have to come to our course named A path to zero failures in tailings facility: what are the success criteria and what is achievable?

Tagged with: mitigative roadmaps, Tailings Mine Waste 16, TMW2016

Category: Consequences, Mitigations, Optimum Risk Estimates, Probabilities, Risk analysis, Risk management, Tolerance/Acceptability