Smart Manufacturing for Economic Growth in South Africa
South Africa’s economy has been given a theoretical boost via its burgeoning manufacturing industry following the inaugural Manufacturing Indaba event in May.
Taking place at Emperors Palace in Ekurhuleni, the gathering was organised to bring together business owners, industry leaders, government officials, capital providers and professional experts to assess the hidden fiscal gems currently being under-utilised within manufacturing, science and innovation.
Esteemed partners comprising Deloitte SA, the City of Ekurhuleni, Productivity SA, Proudly SA, SEIFSA, NCPC-SA and Manufacturing Circle have subsequently produced a Declaration of Intent to ensure that the country delves deeper into its resources to produce the next generation of manufacturing talent; for the benefit of the industry, and for the country as a whole.
Declaration of intent
The two-day event’s location in Ekurhleni, in the Gauteng region of the country, was especially pivotal in the overall plans emanating from the discussions, with the region earmarked as a key area of a potential revival, through an industrial development zone.
City of Ekurhuleni has taken a deliberate trajectory towards the development of an Aerotropolis, a first of its kind in Africa. The Aerotropolis planning lies at the heart of the Cities next phase of globalisation and development, with the manufacturing sector playing an important part in this development. Meanwhile, Gauteng’s MEC for the Department of Economic Development, Mxolisi Xayiya, addressed delegates on the “Proposed Growth and the Roadmap for Developing Manufacturing in Gauteng”.
“One thing I’ve found in common amongst those who attended the Manufacturing Indaba is that everyone – from government to the private sector - is looking to the manufacturing sector as that next big growth frontier,” said Ekurhuleni’s HOD for Economic Development, Caiphus Chauke.
Executive Mayor of the City of Ekurhuleni, Cllr Mondli Gungubele added: “The City of Ekurhuleni’s participation in this Inaugural Manufacturing Indaba has been important for our prospects of developing the region and our plans to revive the manufacturing sector.
“I was quite impressed with the turnout at the inaugural Manufacturing Indaba and there is significant scope for further developments. The discussions were robust and there was a clear demonstration that everyone understands the importance of the role manufacturing has to play in the fight in turning the economy of the country around and improving the general living standard of all our people.”
Apart from being endorsed by the City of Ekurhuleni, the Manufacturing Indaba was also supported by strategic knowledge partner, Deloitte and Productivity SA, as well as being endorsed by Manufacturing Circle, and hosted by Siyenza who is looking to build on its successes in hosting the Africa Energy Indaba, the continent’s premier energy event.
“We are very pleased with the launch of the Manufacturing Indaba because we see the growth potential for job creation and skills development of this sector,” said Liz Hart, Managing Director of Siyenza.
“The success of our nation depends on a strong and innovative manufacturing base with Deloitte on board as our knowledge partner we believe we can leverage this powerful collaboration of strategic partners to promote prosperity through manufacturing, science and innovation.”
Localisation as a global trend
As the country’s second largest economic sector, manufacturing did experience a slight year-on-year rise in 2013, but the general consensus is that more needs to be done to eliminate the obstacles that local manufacturers have typically had to face to remain competitive with counterparts in neighbouring countries.
Drivers such as innovation, costs of labour and materials, supplier networks, economy and trade, infrastructure and government investments are all seen as key instigators in bridging this gap and helping the country climb out of the doldrums through enhanced education and security.
Localisation as a global trend was discussed in detail while other key topics addressed included upcoming challenges to the industry, the opportunities for SMEs, incentives to ensure foreign investment, access to finance and general growth strategies in enhancing a culture of productivity.
No stone unturned
As well as formulating potential solutions, the idea behind Manufacturing Indaba has also been to raise awareness to some key groups in South Africa; namely policy makers, private equity investors, international exporters and suppliers, and academic bodies and institutions.
This has seemingly been achieved via a focus on three separate ‘clusters’, targeting various sectors of industry.
Cluster one consisted of a more qualitative focus on the potential of metals fabrication, transport equipment, oil and gas, energy and agro processing while cluster two comprised automotive sectors as well as chemicals, textiles, paper, packaging and biofuels.
More advanced manufacturing engrained into the likes of aerospace, defence and nuclear sectors were also accounted for in the third ‘cluster’ with no stone being left unturned as part of the overall strategy.
The hope now is that the country, and subsequently the wider continent, will enjoy the same successful outcomes from the Manufacturing Indaba as have been seen in its Energy equivalent.
One thing is certain though, with the clout of the partners behind the initiative, the aim of moving the industry forward over the next five years, and making manufacturing a more attractive prospect for locals in Africa, could not be in safer hands.
5 Minutes With PwC on AI and Big Data in Manufacturing
Please could you define what artificial intelligence is, and what Big Data is?
AI is the ability of a machine to perceive its environment and perform tasks that normally require human intelligence, and it’s a whole field of different technologies, techniques and applications.
Big data is a set of tools and capabilities for working with, for processing, extremely large sets of data.
How does AI and Big Data work together?
Big data is just one of the enablers of AI, though as we see increasing volumes of data, it’s one of the most important
How can this be applied to a manufacturing setting?
Broadly speaking, there are many benefits of AI, and the use of data, which include reducing costs, minimising human error, and increasing productivity and efficiency. The important thing to consider is any setting - for the use of any technology - is what is the problem you are trying to solve? Be it merely automating repetitive tasks or to reinventing the nature of work in factories by having humans and machines collaborate in order to make better and faster decisions.
Why should manufacturers use AI and Big Data when adopting smart manufacturing capabilities, what is the value for manufacturers?
One view is, again, the economic benefits of AI, which come in manufacturing as a result of:
1. Productivity gains from automating processes and augmenting the work of existing labour forces with various applications of AI technologies.
2. Increased consumer demand due to the increased ability to personalise and tailor manufactured products, along with higher-quality digital and AI-enhanced products and services.
Manufacturing (and construction industries) are by nature capital intensive, and in our 2018 report, “The potential impact of AI in the Middle East,” we estimated that the adoption of AI applications could increase the sectors’ contribution to GDP gains by more than 12.4% by 2030.
How can AI and Big Data help manufacturers to evolve in the Industry 4.0 revolution? What about those already looking at Industry 5.0?
It’s really about the investment you make now, in order to futureproof your business.
We typically see two broad strategies or approaches to the adoption of AI. There are things that we can do immediately, without any recourse to Big Data - which is to adopt technologies we describe as Sensing, those involving computer vision, for example. There are plenty of use cases where these can be used immediately in manufacturing, such as for automatic fault detection. However, there is a longer term play which requires investing in data - getting the right collection mechanisms in place, storage, data governance, Big Data capabilities etc - in order to develop increasingly valuable machine learning driven AI use cases. This is absolutely necessary for long term adoption success.
What is the best strategy for organisations looking to realise the value of AI and Big Data in manufacturing?
AI and Big Data are only one part of a successful smart factory. The organisations that lead on AI adoption are those who have already made the most progress in digitising core business processes. In order get ahead in using AI solutions at scale, there are a number of technology investments and organisational decisions to be made, including:
1. Digitising processes ultimately leads to improved ability to generate data, and in the manufacturing setting - with many 100s of sensors generating 1000s of measurements in real time, the result is Big Data. Data is key to building AI so reliable and accurate data acquisition, management and governance are key. The production line and factories play a critical and direct role in the data-acquisition process.
2. AI strategy, both long and short term, begins with the use cases, the business applications. Manufacturers need to ask where they want to use AI and gather these use cases together and prioritising projects based on a balance of expected impact and complexity of implementation.
Of course, in addition to technology and business processes, people are at the heart of any successful technology adoption. AI teams need to be composed not only of data scientists, also data engineers and solution architects to enable their work, data stewards to ensure accuracy, and increasingly so call “Analytics/AI translators” who are able to communicate with business leaders and technology experts. Culture is also key, and manufacturers need to enable a data and AI-driven culture, building trust in data and algorithms by educating their workforce about AI and its capabilities, how best to extract value. It’s not just the positive of course, but also the risks and limitations, as these when encountered without expectations having been set, can significantly impact willingness to invest.
What are the challenges when it comes to adopting AI and Big Data in manufacturing?
has shown that one of the major challenges to implementing AI is uncertainty around return on investment (ROI). As I said, there is significant investment required for a long term data and AI strategy to be successful, and expectations around the time to see tangible returns must be set realistically.
Many companies also struggle with the data side: collecting and supplying the data that an AI system needs to operate, and ensuring that it is accurate. Again, this speaks to the bigger investments required in digitisation.
Some of the main challenges for manufacturing companies with implementing AI at a scale from our research include:
- 40% → Technologies not mature
- 40% → Workforce lacks skills to implement and manage AI
- 36% → Uncertain of return on investment
- 33% → Data is not mature yet
- 32% → lack of transparency and trust
- 24% → Work councils and labour unions
- 22% → Regulatory hurdles in home & important markets
One element highlighted here, particularly around lack of trust, and labour unions, is that AI is typically misrepresented in the media as “replacing” workers, and taking jobs. Yes, there are efficiency gains to be made from automation, as there have been since the first industrial revolution. But we believe that Data and AI are at their most valuable when they are used to augment workers, enhancing their abilities and the products being manufactured.
Another challenge we’re starting to see emerge is cyberattacks increasingly targeting interconnected equipment and machinery in smart factories. PwC recently hosted a webcast, in cooperation with the National Association of Manufacturers in the US and Microsoft to discuss this.
What are the current trends in AI and Big Data in manufacturing?
- We see companies putting slightly more focus on adding AI solutions to core production processes such as the engineering, and assembly and quality testing
- Safety is of significant importance, with techniques adopted in protocol adherence capabilities (for example maintaining safe distance from specific machinery) being adopted in more every day scenarios for COVID-19 protocol adherence
- There is considerable interest in predictive maintenance for large machinery involved in manufacturing processes, and also supply-chain optimisation
What do you see happening in the AI and Big Data industry in manufacturing in the next 12-18 months?
Honestly, I think we’ll see a continuance of where we’ve already been going for the last 12- 18 months. AI and data are already being used in manufacturing but this use doesn’t get as much attention in the media as, say, healthcare, but the success stories are there, and they will continue as operations continue their digital journeys.