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Predictive analytics is a powerful tool to help manufacturing companies make better decisions and improve efficiency. It provides a competitive edge for organizations in the manufacturing industry. It can help manufacturers identify new trends and opportunities and address challenges with an efficient solution.

Predictive analytics can forecast demand, manage inventory, and predict maintenance needs to minimize downtime. It is also used for quality control by identifying defective products before shipping. It is an excellent example of how data science can be applied to business problems to increase decision-making effectiveness.

Predictive analytics uses statistical techniques to identify patterns in data and use this information to make predictions. It is a powerful tool that can help manufacturing companies predict demand and make better production decisions. Accordingly, IDC estimates that spending on AI-powered applications, such as predictive analytics, will increase from $40.1 billion in 2019 to $95.5 billion by 2022.

Some advantages of predictive analytics

1. Predict performance by detecting patterns

Predictive analytics can filter through massive volumes of historical data far faster and more precisely than humans. We can enhance output by 10% without losing first-pass yield by using machine learning technology to recognize recurrent patterns and other connection factors.

AI and machine learning can look for trends and combine them to assist your company in uncovering possible efficiency gains, foresee problems, and cut costs.

2. Analyze market trends

Another application for PA is forecasting customer demand. Knowing what to expect in the future might help you determine what to do next.

Every business conducts some manual market research. For example, some consumer items are seasonal and sell better at certain times of the year. Demand forecasting may be aided by predictive analytics using statistical algorithms, which isn’t a new concept.

Customers’ future purchase patterns, supplier connections, market availability, and the impact of the global economy are all influenced by a variety of variables. The only way ahead is to manage them all through PA.

3. Assists with inventory management

Supply chain management—stocking raw supplies, keeping completed goods, and coordinating transportation and distribution networks—is a complex commercial process that necessitates significant training, data from several sources, and excellent decision-making ability.

A computer model based on your data, on the other hand, may help supply chain managers make more confident and precise judgments. For example, such a model may ensure that you are never overstocked, understocked, or overburdened with unsaleable goods, even determining the best positioning of things on your shelves.

4. Enhance the product’s quality

There are make-or-break steps in every manufacturing process where overall product quality is determined; these are frequently handled by humans who are prone to error. Artificial intelligence (AI) and machine learning are cutting-edge alternatives to this problem. Sensitive manufacturing stages can be delegated to robots that use machine learning to improve with each use. When compared to human-made items, this results in higher product quality.

PepsiCo, for example, has used machine learning systems to improve how it makes one of its famous Lays chips, from estimating potato weight to examining the texture of each chip with a laser system. These have resulted in a 35% increase in product quality.

Conclusion

Predictive analytics is undoubtedly a key boon for manufacturers as it can help them identify new trends and opportunities and address challenges with an efficient solution. It can also help manufacturers understand their customers better and create products that will be successful in the market.

The manufacturing sector’s technological developments are critical to the global economy’s progress. Manufacturing innovations that improve the productivity and long-term viability of entire production processes are the newest manufacturing trends. On the other hand, manufacturing companies are looking to retain productivity with a smaller workforce in the aftermath of the COVID-19 outbreak. As a result, startups are working on smart sensors, immersive technological devices, and wearables that eliminate the need for workers to be physically present.

Industry 4.0 technologies are changing how the manufacturing industry works, making them more agile and resilient than ever before. While it’s easy to get caught up in the whirlwind of change, it’s also important to step back and consider the big picture. In 2022, the manufacturing industry is projected to see specific changes that, if properly utilized, can stimulate innovation and help organizations stay competitive. This blog will cover several key areas for manufacturers to focus on, in-order to shape 2022 and beyond.

Industrial automation

Although automation is not new, it has become more accessible, simple, and cost-effective since the development of robotic technology. It has also reduced and eliminated possible risks to human life, making the manufacturing process safer. Intelligent automation is a critical technology that will change the manufacturing industry because it simplifies numerous material handling, assembly, and painting processes.

According to the Industrial Automation Report 2021-2028, the global industrial automation market is expected to grow at a CAGR of 9.2%, from USD 191.74 billion in 2021 to USD 355.44 billion in 2028.

Additive manufacturing (3D printing)

Manufacturing will be transformed in the future years by additive manufacturing. Design freedom, higher-performing goods, enhanced plant productivity, sustainable procedures, and a shorter time to market are all advantages that come at little or no extra cost.

Aerospace and defence are at the forefront of additive manufacturing, closely followed by automotive production.

Xact Metal is a 3D metal printing startup based in the United States. The printers’ high-speed digital galvanometer system allows faster metal additive manufacturing printing. The solution 3D prints components in various metals and comes with software that makes machine setup, control, and monitoring a breeze.

Machine Learning and Artificial Intelligence

Artificial intelligence (AI) is intelligence that can mimic human cognitive abilities. On the other hand, machine learning (ML) refers to computer learning or improving performance by analysing and understanding data. Machine learning technologies are utilized in real-time in AI to allow factory machines to fulfill their tasks. Simultaneously, machine learning can be used in data science to evaluate the obtained data to uncover patterns and create future predictions, enabling you to build a smart manufacturing industry.

AI aids in the improvement of product quality and leads to market adoption. While AI, machine learning, and data science may sound similar, each has a distinct role and effect in the market.

Zeominds is a new AI-based product and service provider established in India. The software analyses machine data from IoT sensors in real-time. It detects signs of failure and deterioration in performance, lowering maintenance costs and enhancing machine productivity in industries.

Supply Chain Nearshoring

In 2020 and 2021, the global supply chain faced considerable challenges. The manufacturing industry will continue to face problems due to supply chain challenges. To address various supply chain difficulties, manufacturers frequently turn to local vendors.

While this may raise product prices, it can also be viewed as an opportunity to improve agility, flexibility, and quality, all of which lead to higher customer satisfaction. As a result of the globalization to localization strategy, on-shoring is expected to continue in 2022. This tendency will hasten the adoption of distributed or local manufacturing, a customer-centric strategy for meeting rising customer demands.

Learn more at Manufacturing IT Summit

Event Organised by Exito Media Concepts

Factory of the future, also called smart manufacturing or Industry 4.0, results from fast-altering disruptive technologies striking manufacturers’ cyclones. Operational technology, as well as information technology, are both observing great advancements and innovations.

The confluence of these two technologies is generating a paradigm transition. As a result, the manufacturing sector is undergoing the fourth industrial revolution.

In Africa, the future of work is playing out moderately different from the occurrence in advanced economies. As a result, new technologies are likely to develop new jobs and boost the productivity of existing ones. Within the world of technology, this section focuses on digital technologies as these technologies have the potential for rapid future generation and are also adopted across the world. This approach also includes the generation and adoption of low-skill-biased technologies that enable low-skilled workers to learn and upgrade their skills on the job.

Recent evidence points to large positive employment effects and no displacement of low-skill jobs in African countries after the arrival of fast internet connectivity. Digital technologies influence employment through a suite of different channels, comprising changes in firm entry, increase in productivity, and changes in exports.

Results of smart manufacturing along with foundational technology- The Internet of Things shows 80% increased efficiency and 42% lesser product defects in manufacturing processes. This approach indicates the best time to invest and implement such technologies is now. As a result, one can expect better growth in the manufacturing sector and a strong boost to the continent’s economy.

Trends and Technologies shaping the African manufacturing sector.

While the specific emphasis is on digital technologies, other technical upgrading categories enable organizations to retain jobs and skills.

Repurposing local items: For example, the global demand for outfits sharply decreased during the pandemic, while Africa had a large demand for personal protective equipment (PPE). In the face of global export bans on COVID-19 essentials, governments supported the repurposing of local manufacturing firms into PPE production. This strategy ensured that skills were being retained for sustainable production in Africa. This scenario was particularly evident in garment companies in the Hawassa Industrial Park and Transgreen in Ethiopia.

Need for Adaptive Innovation: In Africa, innovation and technological development have mostly relied on governments providing the enabling business environment, investing in research and development (R&D), and supplying the analog complement, for example, electricity and the regulatory framework (top-down model). However, the private sector can implement adaptive innovations and inventions operating in an entrepreneurial model and often sponsors development partners (bottom-up model).

Expanded use of digital technologies: Many industries expanded the use of digital technologies in response to the pandemic. The survey conducted by Business Pulse of 18 countries in Africa shows that 22% of organizations either started or increased the use of the internet, social media, and other digital technologies. The intensity in the use of digital technologies was higher in financial, manufacturing, information, and communications services. Over time, a greater percentage of Kenyan associations adopted digital technologies in response to the pandemic, especially among manufacturing firms and small firms, driving increased sales and employment in these countries.

Learn more at: Manufacturing IT Summit – Africa Edition

Event by Exito Media Concepts

Africa is now seen as a continent full of growth opportunities, especially in the manufacturing sector.

Fuel, food and beverages, chemicals, glass, ceramics, and cement form the bulk of manufacturing industry in the continent. As part of post-pandemic recovery and increase in demand, the manufacturing sector is expected to hit $666 billion by year-end.

There is certainly a high need to empower manufacturing stakeholders in the continent to enter the new age of innovation and technology and ensure better sustainability to compete in production and trade with western countries.

Potential for Africa’s manufacturing sector in the world

In Africa, the average age group of people from 14-24 years are expected to grow more than double this year compared to 2015. Hence, one can expect high growth in the youth and thus a direct result in robust growth in the manufacturing sector. Countries like Uganda, Tanzania, etc. have also witnessed the interest of investors in varied sectors. The Free Trade area launch in 2018 has been another significant step towards encouraging manufacturing and industrialization in the continent.

5 digital transformation strategies that could boost growth in the manufacturing sector in Africa

1. Hybrid Future Work

Organizations should adopt a hybrid/ blended workplace model to maintain mobility. The hybrid workplace model is a combination of both remote and office work together. It gives employees the flexibility to work in both environments. Much like the rest of the world, Africa’s manufacturing sector will greatly benefit from a hybrid work model. This model empowers employees with access to individual tasks with automated workflows coupled with the physical office for collaborative tasks with peers and groups.

2. Cloud Computing

The future workspace aligned with cloud computing is one of Africa’s key industry technology trends in 2021. It will enable businesses to stop investing in costly infrastructure. Instead, businesses can already implement cloud computing in the workplace, storing their data in highly secured cloud systems. Only authenticated users can access and edit information on it anytime.

3. Automation

Automation equipment aid in automating the activities and measure performance. Automation enhances the efforts of the workforce that in turn drives productivity. Automation can even facilitate the creation of new job positions. The critical, regular operations can also be efficiently handled through automated processes without errors. Digital Twin Technology is yet another application of automation that is gaining traction in product development and business performance improvement.

4. Bringing your atmosphere into the remote workforce

The significant obstacle of current periods is that the businesses are exponentially shifting towards a remote workforce . It has sustained business continuity and has given employees the flexibility and accessibility to be productive. So, Bringing-Your-Own-Environment gives employees the freedom to be reliant on the remote working system. This increases productivity and ensures a better employee experience.

5. Creating a compelling employee experience

Organizations should host training and development workshops and modules to train employees at their own pace. Employees should have the freedom to use social media systems to voice their ideas and opinions related to tasks and operations, ensuring a transparent workplace. When employees work remotely, organizations also need to showcase periodic feedback and training to keep them motivated.

The aforementioned digital transformation strategies can certainly drive growth in African manufacturing sector, while propelling them towards a better future.

Learn more: Africa edition-Manufacturing IT Summit​