THE manufacturing industry’s role in the Namibian economy has seen a long and sustained still birth that has not produced enough to defend its very existence. Job creation has also not materialised and the sector which is the cornerstone of the growth at home initiate needs something special to gather strength.
However, aside from a single line about focusing on education as an essential service and “promoting high standards instead of high pass rates”, there seems to be little to no acknowledgement that for Namibia to become a globally competitive manufacturing hub, it needs skills that can interface with the technologies driving global manufacturing progress.
Instead of relying on a large pool of labour, which was until quite recently the hallmark of the South East Asian sector leaders, modern manufacturing is capital intensive – with a focus on using technology to improve production. New, more efficient production technology requires fewer but much more highly skilled workers to operate – the promise of ‘a million jobs,’ then, is a false one, at least for any country wishing to compete at a global level.
Imperatively, manufacturing productivity leveraging next-generation technologies such as IoT, big data, machine learning, and robotics has increased productivity so much that it is currently outpacing demand.
Modern manufacturers are all focused on three key priorities: speeding up production, improving the quality of manufacturing output, and reducing cost. In this, machine learning and AI are emerging as the go-to technologies for driving enhanced process efficiencies while lowering operational costs and maintaining global quality standards.
Machine learning can serve as a powerful tool in large, sophisticated manufacturing operations. Its power lies in the ability to examine process data and extract patterns and relationships without imposing any adjustments to the production process, the outcomes of which can augment production processes to achieve higher yields.
While most manufacturing operations are different, all have rudimentary data infrastructure that can be processed and mined for value by skilled data scientists. A single view of all operational data helps to reduce the complexity of managing multiple types of data and assists in the development of a set of prescriptive models that can help manufacturing processes move toward deeper forms of automation.
Right now, the dire lack of skills in Namibia is undermining industry-wide efforts to revitalise the local manufacturing sector, while the global manufacturing leaders are powering ahead with a lean but highly skilled workforce.
Machine learning is a transformative technology that can put the Namibian manufacturing sector on par with the best in the world. But without the requisite skills, manufacturers will struggle to realise its full potential.
The sector should prioritise skills development over mass job creation, and work with experienced technology partners who can deliver rapid productivity gains while helping build a roadmap to survive the ‘fourth industrial revolution’.
Confidente. Lifting the Lid. Copyright © 2015