In its study “Disruptive forces in the industrial sectors”, the management consultancy McKinsey & Company states, from a worldwide survey of more than 300 top decision-makers from industry, that 3 out of 4 managers assume the speed of change in artificial intelligence and the Internet of Things to be an essential factor in changing business models for their industry. Traditional companies are poorly prepared for new digital business models, and there is a lack of skilled and talented staff.
According to the study, the drivers for the changes are 1) the much larger and constantly growing data, 2) the exponential increase in the computing speed of computers, and 3) the worldwide networking of machines, equipment and devices – this is how around 20 billion devices are combined on the Internet and another 50 million are added daily. This results in innovations in quick succession.
What does (digital) disruption mean? This is generally understood to mean the process by which existing structures, organizations and business models are broken up. The subsequent innovation here creates new products and structures, new working methods and processes. It is therefore not a matter of further development or evolution, but of a new development or revolution that displaces or permanently changes the existing.
A well-known example is the iPhone, developed by Apple, with which he first changed (revolutionized) the market for mobile phones and then the distribution market for music and films via the iTunes platform. Other examples in the emergence are e-mobility and 3D printing.
Disruption is therefore synonymous with fundamental and competitive innovation.
In industry – predominantly in mechanical engineering – digitization has arrived at varying depth in many areas – in production (control of materials and machinery and plant control, condition-based maintenance, energy management), in logistics control and optimization of warehouses and material flows u, in sales and marketing (recording of customer wishes and requirements) and in services (maintenance, servicing, spare parts supply).
Business processes and procedures are automated using digital data. In many cases, however, still classically hardware-oriented.
What about mining?
Digital disruption has also arrived in mining. Operational challenges due to rising labour and energy costs, low material content of the deposit, longer transport distances, higher quality requirements of the customer, price volatility of the sales product and above all due to time-consuming procedural obstacles in the approval process force the mining industry to increasingly deviate from conventional procedures and to permit innovative measures. It should be emphasised that even in the past mining was characterised by innovations – in the sense of evolution instead of revolution. It focused on hardware-based, more powerful machines and equipment and the automation of certain sub-processes, especially where employees had to do heavy and dangerous work. In mining planning, 3D deposit models are part of everyday life today, as are satellite-controlled dispatch systems in large opencast mines to control the expensive investments for development and machinery. However, many of the data that are certainly generated are still not systematically recorded and evaluated.
Disruption in this industry must therefore be pursued even more vigorously than before. It is not enough for every company, whether producer, supplier or service provider, to march on its own, as it has done up to now, and to limit itself to the established machines and processes. The digital data and information is not only available in the silo, but must also be viewed throughout the entire process – on and across the machines and equipment. Using modern data science techniques, machine sensor data can be linked with quality data along the production process to control production and quality. The localization of man and machine increases occupational safety. Communicating and transparent systems avoid a cost- and time-consuming monitoring and controlling process.
In the future, mining companies, manufacturers of mining machinery, equipment and components as well as service and software providers will need to work hand in hand and in a collaborative approach to bring together their respective expertise and experience to deliver innovation as quickly as possible.
Young startup companies worldwide are revolutionizing the traditional mining industry with their fast and unconventional approach and the use of state-of-the-art data science techniques. This is also necessary, as Bernd Heid, co-author of the McKinsey study, explains: Companies that do not actively tackle this change risk being pushed out of the market very quickly.