Meganika Pty (Ltd) 2015/349583/07

Physical/Postal 4 Seaview Road Private bag X12

Golden Acre Somerset West

Somerset West 7129

7130

Banking Details Bank: First National Bank

Branch code: 200912

Account type: Business cheque

Account number: 62582068427

Contact Dr Gerard van Harmelen CEO +27 83 407 5862 gerard.van.harmelen@meganika.com

Vincent Ellerbeck Technical Director +27 83 306 3084 vincent.ellerbeck@meganika.com

André Potgieter Operations Director +27 72 398 2375 andre.potgieter@meganika.com

COMPANY VALUES

At Meganika we commit ourselves to operate with extreme ethics, transparency, honesty and integrity.

To this end we commit to ensuring that:

Pricing is fair and reasonable and market related;

We remain focussed on quality, even if it is slightly more expensive, rather

than deliver a "quick-and-nasty" solution;

Manage customer expectations honestly and never over- promise;

Inform customers of risk items as soon as we become aware of these;

Establish a culture which goes against a "that's not my job" attitude;

All employees have superior tools, training, enough time and the opportunity

to deliver their best;

The work-life vs. home-life balance is maintained and that work-life patterns

contribute to our families remaining healthy and intact;

To operate according to governmental rules and guidelines, and to be an

example of an excellent corporate citizen.

BUSINESS

Our business consists of adding value to our clients in the minerals processing environment through competent execution of engineering and build activities.

We have solid engineering capability specialising in mechanical, electrical and control disciplines.

We also poses very strong data analytics capabilities for analysis and optimisation of real-time processes using for example, logged data from Scada systems, production and maintenance records and mine plans.

We can accommodate turnkey projects to a maximum value of R5, 000,000.

SPECIFIC CAPABILITIES

Mechanical Engineering

Machine design and integration into plant layout in a true 3D environment

using Autodesk Inventor;

Design of fit-for purpose equipment, not available off-shelf from vendors;

Finite Element Analysis stress analysis including static, dynamic and non-linear

work utilising Strand7;

Heat transfer capability and thermal stress calculation;

Correct materials selection and heat treatment condition for critical

machined components;

The use of correct welding procedure specifications (WPS), procedure

qualification records (PQR) and welder qualification records (WQR) as may

be required in accordance with the relevant design code, e.g. ASME BPVC

and ASME 16.25 as well as AWS D;

Storage Tank Design to API 620/650;

Conveyor Design to internationally accepted standards;

Material transfer point layout and design;

Bin and silo design;

Pump and line selection;

Pumping flow systems analysis;

Pipe design and stress analysis to ASME B31.3 compliance.

Electrical, Control and Instrumentation

Medium and low voltage (MV&LV) power distribution and MCC design;

Design, programming and commissioning of the following PLC, software and

SCADA systems:

Siemens PLC’s: S5-155, S7-300, S7-400, S7-1200 Software: Simatic Manager, TIA Portal SCADA : WinCC Networks : Profibus PA, Profibus DP

Rockwell PLC’s: Allen Bradley MicroLogix,

Allen Bradley CompactLogix, Allen

Bradley ControlLogix

Software : RSLogix 500, RSLogix 5000

SCADA : FactoryTalk View

Networks : ControlNet, DeviceNet

Schneider SCADA : Citect, Wonderware Intouch

Quality Management

At Meganika we take Quality management very seriously. We recognise that QM is a process of continuous improvement. We strive to evolve, document, and abide by quality management systems (e.g. ISO9001), in order to deliver documented, repeatable, transparent and honest technical and financial management.

Archiving;

Document control;

Engineering and design documentation;

Communication management;

Technical workflows;

Non-technical workflows.

Fabrication

Meganika possess the skill set to efficiently supervise the entire fabrication and

machine build process. This includes:

Production of shop detailing drawings and bills of quantity;

Setup and monitoring of fabrication quality control environment (databooks,

QCP’s, certification);

Expediting of work in progress;

Supervision and assembly and factory acceptance tests (FAT).

Installation and Commissioning

Meganika has access to the skill set to supervise the complete on-site installation and commissioning process encompassing the following:

Site establishment;

Build and Commissioning and check points (C1-C4);

Punch listing;

Assembly of Final databook and handover certificates.

Mineral Processing Data Analytics

Background

Mineral processing companies are now, more than ever, being required to achieve new levels of operational maturity and drive process improvement across their entire value chain. They furthermore have to achieve this in the face of greater demand, lower commodity prices, and an ever dwindling supply of experienced human resources.

Advanced Mineral Processing analytics techniques can however make unprecedented contributions to assist in overcoming such fundamental challenges, and it achieves this by applying data techniques not previously applied in mineral processing.

Often, decisions are usually locally optimised but do not achieve optimum capability for the entire value chain. Although more information may be collected more than ever before, it is notoriously difficult to link many sources of data together in the same place, sometimes even in real-time, such as plant behaviours, maintenance, planning, performance, logistics and engineering data. Consequently complex analysis of data has always been time consuming requiring specialist skills and knowledge, and is often neglected in the decision-making process.

The current availability however of more advanced, cheaper (often free) tools, access to advanced computing infrastructures in the cloud (often at fractions of the cost than owning the computers), is enabling analytics to close the loop between analysing data, modelling, simulation, designing and taking action.

Mineral processing plants are rapidly becoming embedded with more and more data flows, instrumentation and on-line monitoring, and embedded sensors. This is driving improved decision making and thus greater control across the organisation, from senior management to operations and maintenance workers.

Given the right models, tools and software, the need for specialist skills and extensive time to analyse data can be minimised. As data analytics becomes embedded in the mineral processing business, decisions are supported by data as opposed to gut feel. Critically, data from many sources can be integrated, sometimes in real-time, allowing rapid improvements in the quality of decision making. Ultimately predictive tools are helping suggest, or even in some cases automate, courses of action.

In minerals processing, opportunities for analytics exist in many areas to allow for the organisation to continue evolving to higher level of maturity. These typically occur in the areas of asset management, planning, and the inbound and outbound supply chain management.

Levels of Analytics

The different levels of analysis, as shown in the following diagram describe both the different levels of difficulty (increasing from left to right), as well as the value that they create for the minerals processing organisation (increasing from bottom to top).

The different stage as describe by descriptive analytics (what happened), diagnostic analytics (why did it happen), predictive analytics (what will happen next) as well as prescriptive analytics (how can we make it happen different).

A more elaborate description of the opportunities for process analysis, modelling, design, optimisation and management are shown in the following table. Whereas business questions are asked towards the top levels of the matrix, the data management, numerics, operational research, and statistics required to affect these are shown in the lower row of the matrix.

DESCRIPTIVE DIAGNOSTIC PREDICTIVE PRESCRIPTIVE

What HAS happened? WHY did it happen? What COULD happen? What SHOULD happen?

What the user needs to DO?

Monitor performance; Explain deviations; Predict infrastructure failures; Increase asset utilisation;

Be aware of exceptions; Clarify and justify behaviours; Forecast demands; Optimise maintenance schedules;

Inform stakeholders; Interpret values/trends; Estimating processing bottlenecks; Optimise flows and buffers;

What the user needs to KNOW?

The numbers and types of failures; What were the causes of this; How to anticipate failures per

asset; How to increase asset

production; What the (maintenance) costs

are; Why did it happen? When to consolidate facilities; How to optimally route trucks/materials;

What the recovery performance is;

Where else, and how often does this happen;

Determine costs of improvements;

What plan will deliver best long term results;

How does Analytics get the ANSWERS?

Standard reporting – what happened; Setting Confidence levels; Predictive modelling – what

will happen; Optimisation – what is the best

possible outcome; Query/drill-down – where

exactly did it happen; Allocating probabilities; Forecasting – what if these trends continue?

Random variable optimisation – what are the variabilities;

Ad-Hoc reporting – How many, where and when; Defining limits or ranges; Simulation – what could

happen next?

What makes this analysis POSSIBLE?

Alerts, reports and dashboards; Correlation and Causality; Predictive models;

Business rules, organisational models, constraints, non-linearities;

Business Intelligence Infrastructure; Hypothesis testing; Time-series analysis;

Statistical Modelling;

Designed to move

The following list of skills have been deployed primarily in the Southern African regional utilities space. However the data management, statistical and modelling techniques used in these areas are directly applicable to the minerals processing environments:

Forecasting: outages, maintenance, weather, tariff, economic, spatial,

short, medium and long term forecasting support;

Resource and Fuel Planning: Loads, supply and fuels, losses and

constraints to be included;

Pricing & Tariffing: Tariff impacts, momentum, technology and

economic impact modelling, simulation, cost of supply studies, price,

income and substitution elasticities;

Primary Energy Optimisation: Fuels, stockpiles, constraints and

scheduling, renewable modelling and losses statistics;

Asset Management: Simulation of stock levels, asset failure rates, repair

times;

Customer Services: Customer behaviour, response and monitoring,

load profile, disaggregation and segmentation modelling.

Visual Analytics: Information visualisation, interactive and graphic

design, data transformations and representation;

Multivariate Statistics: Principle components, factor analysis, cluster

analysis, discriminate analysis.

Time Series Analysis: ARIMA, spectral analysis, error correction models,

various exponential smoothing methods;

Machine Learning: Decision trees, artificial neural networks, genetic

programming, Bayesian networks, simulation and optimisation;

Designed to move

Correspondence Analysis: Contingency tables, multiple

correspondence analysis, categorical data.

Designed to move

KEY STAFF

Dr Gerard van Harmelen

Gerard is known as a mover and shaker in industry and has successfully initiated and run several companies and ventures. He is qualified as an electrical engineer and has a wealth of experience in business set up and management. He also has vast experience in data analytics.

Vincent Ellerbeck

Vincent has many years’ experience in the mining industry and has worked at several EPCM design houses. He is a very experienced mechanical engineer and is professionally registered with ECSA since 1994.

Alan Solms

Alan brings a wealth of experience in control and instrumentation. He has well over twenty years’ experience over a wide range of projects.

Designed to move

Bryony Pienaar

Bryony is a dynamic young mechanical engineer with solid experience as project package engineer covering mechanical equipment sizing and selection, small component design and overseeing of draughting, project management and quality control.

André Potgieter

André is a highly experienced operations and facilities manager having managed a range of operations including fleet management, logistics, finance operations and business development administration.