How AI-powered Tools are Changing the Face of Manufacturing Industries
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How AI-powered Tools are Changing the Face of Manufacturing Industries

October 20, 2022

7 min read

Mike Thorpe

Mike Thorpe

The impact of artificial intelligence (AI) is far-reaching and is drastically changing the way we live and do business. AI-powered solutions are making their way into smart products and services, as well as into everyday company operations, like managing stakeholder relationships. AI holds the potential to streamline work, boost efficiency and production, and it is already having a positive effect on key growth metrics across industries. Soon this increasingly popular choice may be indispensable to competitiveness.

However, beyond the proven effectiveness of the technologies themselves, the success of applications of AI and ML tools in businesses will depend on implementing them through appropriate strategies with a clear understanding of the priorities unique to each company, industry, and nation. 

In this article, we will look at how AI and ML tools are reshaping manufacturing industries, and reflect on how companies in Africa and developing nations can learn from the latest research to take advantage of this opportunity.


A Brief Overview of Artificial Intelligence

Artificial intelligence (AI) is a field within computer science that has multiple definitions. Broadly, the term is used to refer to machines and cloud-based technologies with the ability to simulate, automate and enhance human capabilities. With increasingly accurate capabilities in computer vision, natural language processing, pattern detection, and more, AI systems, driven by algorithms and statistical models, are getting better at reasoning, decision-making, and problem-solving, toward specific goals. 

Machine Learning (ML), a subset of AI, is the basis of tools that thrive on massive amounts of data. These pattern-recognizing tools are being trained by data scientists and software engineers to solve increasingly complex challenges, and to use their own experience (data) to improve their own abilities –sometimes without much human intervention. Today, AI is used in a variety of ways, from powering search engines and making relevant movie recommendations on Netflix, to optimizing stock portfolios, guiding self-driving cars, spotting fraudulent payments, and early detection of breast cancer.


AI in Manufacturing

Although AI has been around since the 1950s, the field has seen explosive growth in the last decade. This is due in part to billions of dollars in investment into research and development, as well as increased computing power and speed, and the proliferation of cheaper systems for collecting, storing, and processing data. In manufacturing, data from massive process monitoring is driving the transition toward Industry 4.0 (I40). This evolution combines advanced production and operations techniques with digital technologies. It is being made possible by smart factories and supply chains equipped to collect and share data along the manufacturing process. I40 is also being enabled by smart services and products, which relay user information back to producers. 

Tesla provides a clear illustration of how the linear nature of the manufacturing industry is being disrupted by AI. While competitors take months to create new designs, Tesla stays ahead by making consumers the starting point of its product development and improvement cycle. The automaker’s algorithms study and process real-time data from its “fleet of over 2 million cars” and relay the insights to product development teams. Thus, AI is changing how parts and products are designed, made, used, and maintained

Beyond design, AI-powered tools can help to manage production chains and optimize production processes. At Amazon, machine learning is being used to improve the efficiency of its warehouses and distribution centers, reducing the time it takes to fulfill an order, improving the way the order is filled, and getting closer to hitting sustainability goals. In 2022, the company reported using deep learning, a complex form of ML, over six years to reduce packaging waste by up to 36%. This equates to more than a million tons of packaging or more than 2 billion shipping boxes

Another important examples are the use of ML in predictive maintenance systems. These systems use historical data and incoming data from sensors that track activities in real-time, to predict when equipment is likely to fail. Hence, maintenance can be scheduled in advance and plans are automatically made to replace needed spare parts. Even the processes of re-installing or replacing broken-down equipment may be assisted through AI. ML tools can make suggestions for optimization by considering data from previous installation experiences, and even experiences from similar enterprises across the industry. As a result, ML can improve availability and reduce downtime, which is critical to reinforcing supply chains.

Perhaps the most discussed applications of AI involve the use of smart systems to automate tedious or repetitive tasks, which tie up human capital. Examples include online vendors deploying chatbots to interface with customers, or manufacturers using robots in their production operations.

Automation gets a lot of pushback because of the justified fear that it will leave millions out of jobs. Even so, there is reason to suggest that automation may actually work to replace tasks, not entire occupations or people. In the United Kingdom, for example, technology helped to create 3.5 million new jobs between 2001 and 2015, even though it contributed to a loss of 800,000. Therefore, companies will benefit most when they are willing to train stakeholders in the skills and resources they need to make use of intelligent tools.

Clearly, there are benefits to embracing intelligent tools to navigate a rapidly changing world, rife with complexity. AI can help to uncover key insights and make predictions that are not obvious to company directors, driving decision-making when markets change, when global supply chains are interrupted, and when customer preferences shift unpredictably. With a little guidance, AI may actually be a way for manufacturing companies in developed nations to refocus team energies toward innovative tasks, and address widening skills gaps and post-pandemic labor shortages.


Outlook for AI-Powered Manufacturing in Africa

Hundreds of AI-powered tools are already being marketed to manufacturing businesses for all kinds of possible solutions. This trend will likely continue, especially as the security of sharing data improves and as the computing tools themselves become cheaper and easier to utilize. 

Still, it is important to remember which players are benefitting first and the most from these technologies. Large tech companies and enterprises based in developed countries have access to huge amounts of real-time and historical data, as well as the resources and infrastructure to develop, install, deploy and manage smart tools. This stands in stark contrast not just to smaller businesses, but to entire developing nations. For this reason, a multitude of actors must intervene if they wish to avoid promoting widespread unemployment, furthering the digital divide, and global inequality.

Africa is a clear example of a data-scarce continent with extremely limited specialized talent and access to research, where the local manufacturing industries have remained largely underdeveloped. The West African region includes Nigeria, Africa’s most competitive player, which contributed 18.4% of the continent’s GDP in 2021. However, “the region is characterized by obsolete capital and facilities” and “is one of the least integrated into the global value chains (GVCs), particularly for processing activities”.  This translates into a strong external dependence on manufactured goods, which, in 2015, represented on average 46% of West African imports. This also translates into clear risks for African nations to stay even further behind the rest of the world if the evolution of companies into Industry 4.0 only occurs abroad.

If local interests are prioritized from the get-go and smart tools are leveraged strategically to boost manufacturing, African nations can reap incredible benefits from AI. In addition to having the youngest growing population in the world, Africa has 60% of the world’s uncultivated arable land. Today, resource-abundant nations are largely focused on agriculture and services, but there is huge potential for turning cash crops into more developed products, which can cater to growing internal markets. 

Local statistics show that the average GDP of households on the African continent has doubled in the past 15 years. Because of this, African leaders are calling on more intra-continental collaboration and for more industrialized countries like Nigeria to strengthen manufacturing and regional supply chains. Although only 40% of Africans have access to the Internet today, the affordability of smartphone devices is increasing internet penetration across the continent, as well as consumer power, while bringing more customers online than ever before. More diversification through industrialization also opens up possibilities for developing products for customers overseas who have become accustomed to online shopping post-COVID-19 pandemic global consumers, and are continuously on the lookout for unique products.

In order to fully benefit from the potential for growth, it seems important for locals to help create an environment where industrialization can move forward and “AI can take root”. One way this could be done is by leveraging strong partnerships between local and foreign businesses, academia, and governmental organizations. Partnerships with the private sector are especially important for access to financing, which will be needed for the type of infrastructural development necessary for industrialization. This includes building roads, modernizing ports, and improving the availability of electricity. Further, alliances with technological giants will also be paramount for gaining access to technological know-how, skills, and tools. IBM Research, Google, Microsoft, and Amazon have all opened AI labs in Africa and are interested in penetrating regional markets.

However, African companies must strive to remain independent, particularly from tech giants, and certainly if development moves forward and becomes easier and cheaper. This way Africans can avoid handing over benefits associated with upping their industrialization. Therefore, alliances with local governments and academia remain key. On the one hand, partnerships with academia can alleviate information gaps and help establish strategies for educating and up-skilling Africa’s population. In 2020, only 28% of Africans had stable paying jobs and youth employment remains a challenge. AI education will be especially important considering that a largely automated AI-powered manufacturing revolution will require workers that are skilled to work alongside computational intelligence.

It’s also critical to mention that allying with governments and public institutions will be necessary for creating a legal framework that can safeguard ethical research, development, and innovation. Most AI-powered tools were developed with foreign interests in mind and include inappropriate biases. Governments can help to guarantee that the development of new smart companies, products, and services will be tailored to serve the local cultures and the interests of the African people. Moreover, government involvement will be essential for lowering all kinds of barriers to collaboration with the private sector but also for the very necessary access to data that will be required to train local ML systems, for data collection purposes. Governments and telecommunication companies are the largest custodians of data on the continent.

Investing in AI Technology for the Future of African Manufacturing

Overall, AI presents a major opportunity to shape the future of Africa, and the people and businesses on the continent would benefit greatly from embracing this chance as they work to improve their societies. The stage is set for an AI-powered industrial revolution in Africa but intelligent tools alone will be insufficient to guarantee growth and competitiveness. 

Development in Africa and elsewhere will certainly require dedicated investment, but it will also require the right intentions, strategic collaboration, informed decision-making, and proper regulation to ensure that African needs come first.

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