Manufacturing 4.0 Relevance to Commonwealth Developing Africa
This section provides background information and analysis of the relevance of Manufacturing 4.0 to Commonwealth Developing Africa, according to UN classification.
These countries are: Botswana, Cameroon, Gabon, Ghana, Kenya, Kingdom of Eswatini, Namibia, Nigeria and South Africa.
Geographically, four of these countries are in Southern Africa, two in Central Africa, two in West Africa and one in East Africa.
This grouping allows for the most coherent analysis given their similar stages of development, similar challenges, and maturity of their manufacturing sectors, as compared to LDCs or SIDS.
Commonwealth Developing Africa member states
Regional Manufacturing Trade & Value-Add
All stats most recent available. Source: World Bank
Manufacturing baseline in Commonwealth Developing Africa
Manufacturing contributes US$145 billion of Manufacturing Value Add (MVA) in the nine Commonwealth Developing Africa countries. This represents 12% of regional GDP, which is less than the 16% of regional GDP in the Commonwealth Developing Asia region.
The nine countries collectively have a merchandise trade deficit, importing US$251 billion of merchandise but exporting US$219.8 billion. The large economies of Kenya and Nigeria account for a large portion of this, with Kenya importing nearly three times more merchandise than it exports, and Nigeria around one-third. Gabon, Ghana and South Africa are the only countries in the region in surplus.
Commonwealth Developing Africa snapshot
- Manufacturing value added (MVA) totals US$142.6 billion, or 12% of total output (GDP) of the nine countries
- Manufactures comprise nearly all of Botswana's merchandise exports (95%) as well as the majority of the Kingdom of Eswatini's merchandise exports (63%)
- Manufacturing value-add contributes to GDP most significantly in the Kingdom of Eswatini (27%) and Gabon (21%), though from small economic bases, as well as in the large economy of Nigeria (15%)
- Nigeria (38%) and South Africa (37%) are by far the largest economies in Commonwealth Developing Africa, and together with third largest Kenya (10%) account for 85% of the collective GDP of these nine countries
- Nigeria (54%) accounts for more than half the population of Commonwealth Developing Africa, followed by South Africa (15%) and Kenya (14%)
- Gabon and Botswana lead the region in GDP per capita at US$8,017 and US$7,348 respectively, nearly double the regional average of US$4,389
Manufacturing value-add contribution to national GDP
Manufacturing contribution to Commonwealth Developing Africa MVA
Manufacturing value-add contribution to national GDP
Manufacturing contribution to Commonwealth Developing Africa MVA
Manufacturing value-add contribution to national GDP
Manufacturing contribution to Commonwealth Developing Africa MVA
Challenges to M4.0 Development
The following provides a series of examples for how Manufacturing 4.0 technologies can address specific industrial challenges faced by Commonwealth Developing Africa.
Many of these countries are much larger in terms of geography, population and economies that Commonwealth LDCs or SIDS, which can significantly magnify or diminish the severity of these challenges depending on national contexts. Attempts are made here to generalise challenges, while recognising the significant diversity of countries and economies in this grouping. Each country will face these challenges in more or less acute ways, as well as face their own unique challenges due to national circumstances.
Developing Africa Regional-level Challenges
- Geography: Developing Africa countries are often faced with challenging geographic circumstances, including distance from main consumer markets and centres of global value chains, as well as lack of uniform access to land/sea/air transport routes.
- Economy of scale issues: Developing Africa countries often have large public sectors which hinder private sector industrial development as wages would be lower in the private sector.
- Competition: several Developing Africa countries have competitive rather than complimentary economic profiles.
- Climate Change: all LDCs face adverse impacts because of climate change, this can hinder foreign investment in these countries.
Developing Africa Country-level Challenges
- Production facilities can halt due to unusual weather conditions, impacting labour availability access to inputs, and requiring repairs to damaged plants and equipment.
- Brain-drain as young labour forces are pulled towards advanced economies where there are greater perceived opportunities.
- Small technical labour forces in several Developing Africa countries can preclude large scale industrial development, despite large populations.
- Complexity of doing business can deter investments in some countries, with most of these countries ranking low in ease of doing business factors.
- Internet access and usage can be a challenge and varies greatly by country, while increasing mobile penetration broadens mobile internet access but does not always equate to internet usage.
- Large public sectors can dominate economies in many of these countries because of diseconomies of scales, which further hampers private sector industrial development.
Example M4.0 solutions to regional industrial challenges
Market size disadvantage
- Potential solution: upgrading and connecting local SMEs to regional and global markets and value chains
- M4.0 application: distributed technologies such as 3D printing allow localised production of textiles, foods containers, components, construction materials, etc, gradually reducing the need for imports of these items
Poor connectivity and logistics linkages
- Potential solution: developing strategic and physical infrastructure to connect to global value chains
- M4.0 application: embedding internet of things (IoT) sensors such as tracking devices enhances transparency of supply chains and readily identify bottlenecks
Lack of economic diversification
- Potential solution: identify new product and market opportunities, prioritising specific sectors
- M4.0 application: climate change concerns will lead to new products being manufactured using clean technology, where enhanced tracking for rule of origin and verified information to consumers becomes more important, including connecting consumer with suppliers through big data capabilities.
Limited sources of economic growth
- Potential solution: upgrading existing value chains, reducing barriers to export competitiveness and opening potential new markets to local businesses
- M4.0 application: digital twins / simulations provide novel revenue streams through for example virtual designs created locally which can then be commercialised via licensing arrangements with countries around the world
Aging population coupled with increasing youth unemployment
- Potential solution: enhancing skills of local populations to improve enterprise productivity and enable a future-ready workforce
- M4.0 application: a M4.0-ready workforce can be developed by supporting local curriculum reform and focusing vocational education on STEM subjects
Limited institutional strength and public sector capacity
- Potential solution: provide competitive advantage to manufacturing sectors by providing industry-specific insights into local consumer demand or anticipating bottlenecks
- M4.0 application: enhance vertical (within a firm) and horizontal (across supply chains) data sharing within industries to create large data pools to leverage big data and analytics applications
M4.0 Application in Commonwealth Developing Africa
Big Data & Analytics
Large amounts of data are analysed by advanced computing technology to provide insights and predictive analysis to support decision making.
Regional Application
Application to large scale production sites which generate significant amounts of data where small efficiency gains will have disproportionately positive impacts. If firms come together to share data, they could distribute the costs for meaningful insights in sectors/countries where cost pressures are an issue.
Autonomous Robots
Autonomous robots are used in manufacturing to hold and move heavy items on a production line and can also help with order picking at the warehouse level.
Regional Application
Although perceived to compete with low wage labour, autonomous robots could significantly enhance efficiency as well as safety, and potentially mitigate regional challenges such as skilled labour shortages.
Simulations / Digital Twins
Real world environments can be simulated virtually, such as entire factory floors using sensors. This allows experimentation, virtual training or exploration without the need to visit or modify real world sites. Additionally, entire product information life cycles can be retained from primary production to end user.
Regional Application
This can be applied to light industrial sectors where efficiencies are crucial to competitiveness. Further applications can include:
- Upgrading existing manufacturing sites to more advanced production methods and processes, without disrupting ongoing operations.
- Sensing soil fertility to maximise agri-production: advanced analytics could determine when to replace older plant varieties for new ones to maintain sustainable plant stocks.
Horizontal/Vertical Data Integration
Large producers have capabilities to share data within their own firm (vertical data integration); further maximised by sharing relevant data with other firms in the value chain such as suppliers (horizontal data integration).
Regional Application
Applications can include:
- At largest firms where it makes sense to integrate large pools of data.
- Manufacturing sectors with long supply chains and export orientation could benefit from shared data, e.g., logistics and tracking information.
- Value added features such sustainable and organic labelling of fishery or agri-produce could benefit from enhanced quality assurance enabled by data integration.
Internet of Things (IoT)
Internet of Things (IoT) is enabled by small sensors with computing capabilities that deliver real-time information. A simple example is the use of radio-frequency identification (RFID) devices to determine how fast a production item is moving, which when combined with Big Data analytics can provide meaningful insights.
Regional Application
There are wide applications for this:
- Large firms can monitor how quickly items are produced and where there are blockages to optimise production set-up or offer enhanced training.
- For logistics and supply chain management, RFID’s can help with real-time location and tracking information.
- Sensors for energy inputs can provide necessary data to enable savings on energy consumption.
Cybersecurity Technology
Cybersecurity technology encompasses anything that protects digital systems from internal and external attack. Modern cybersecurity involves technology such as blockchain or artificial intelligence to protect infrastructure and technology such as IoT devices.
Regional Application
This would benefit production processes where digital assets are important, such as:
- Designs in clothing and apparel sector
- Digital creative designs
- Payment systems, especially in the context of international trade of goods.
Additive Manufacturing
This technique involves adding layers of material to create a finished product, and is also known as 3D printing. This contrasts with traditional processes where manufacturing has been based on subtractive methods such as cutting from fabric, removing wood etc.
Regional Application
Applications include:
- Replacing imports of small parts and components with local produced/"printed" alternatives.
- In clothing and apparel sector, shoes and clothing could be manufactured using synthetic materials.
Artificial Intelligence
Artificial intelligence and machine learning allow machines to use algorithms to process data and reach conclusions that were not originally programmed into them. It is used in manufacturing for demand forecasting and predictive maintenance, among other applications.
Regional Application
AI applications can assist in providing more advanced insight and visibility into operations, increased automation of processes, and greater forecasting and prediction capabilities.
Augmented Reality
Augmented reality utilises extra sensory virtual input, usually visual, overlaid onto the actual world.
Regional Application
This has use potential in more advanced manufacturing sectors, allowing physical and virtual information to concurrently exist in the workspace, helping to follow work or assembly instructions, detect defects, or enhance sales and marketing functions.