How to Digitally Transform Your Manufacturing Business

News of countries boosting their domestic industrial capacities and manufacturing capabilities are today’s top stories. Some latest developments include the CHIPS and Science Act in the US that allocated $57.2 billion for semiconductor manufacturing; the European Green Deal that aims to drive the EU’s sustainable transition; and a 500 billion yuan fund in China which focuses on strengthening SMEs in the technology sector.

While the global manufacturing sector expands and continues to attract investments, the need to prioritize green technologies also grows. In 2023, manufacturing contributed 23% of greenhouse gas emissions. Technology developments like artificial intelligence, machine learning, etc. are integral to innovation, efficiency, quality control of products and services, and achieving sustainability commitments in the manufacturing sector.

Yet we also need to understand how the manufacturing sector will address labor shortages, upskill its workforce, work around supply chain disruptions, and become more sustainable. And, given the recent events, how can this sector stay competitive in volatile times?

This blog discusses the impacts of five key technologies, their various applications, and how you too can adopt these technologies in your operations.

Cloud migration in manufacturing empowers core issues such as scalability, data accessibility, security, flexibility, and collaboration between teams and various factories.

The Cloud also enables manufacturers to:

• Expand globally, secure in the knowledge their data is accessible regardless of physical location.
• Provide multiple security layers for data protection.
• Facilitate closer team collaboration with data visibility and sharing.

A food manufacturer’s Australia and New Zealand-based operations experienced production inefficiencies and higher operational costs due to system integration issues. Fortude worked with the manufacturer to implement a custom cloud solution that improved their production processes through comprehensive supply chain visibility, efficient inventory management, and manual process automation.

Shifting towards more sustainable manufacturing processes depends largely on data-driven insights into production. This means more accurate demand planning, insights into customer preferences, historical sales patterns, etc. Enterprise Resource Planning (ERP) software plays a key role here as it enables data centralization to give you a complete view of all your data and trends to support forecasting. Manufacturers can alter production capacity as needed with real-time data on inventory levels, order numbers, and storage operations.

Case Study: Fortude worked with a Southeast Asia-based animal feed manufacturer with 22 production facilities and global operations to implement an ERP system that addresses productivity, efficiency, cost, and waste management. Now, the ERP system gives them a centralized portal to manage global operations and scale future growth, improved access to financial data to support decision-making, and streamlined reporting and analytics capabilities.

Predictive analytics also play an important role in machine maintenance. Factory owners have knowledge of which machines are functional, and they can prevent unnecessary downtime by temporarily retiring faulty machines for maintenance prior to breakdown. A Ford factory in Valencia, Spain, deployed a data analytics system that sends real-time updates to engineers about which components are not functioning optimally via a mobile app. This system resulted in significant cost savings and on-time production.

A recent Financial Times article anticipates that over 80% of manufacturing facilities could use AI in some capacities in the coming decade.

Sensors in manufacturing machines generate data, all of which are collected and used by Artificial Intelligence (AI) and Machine Learning (ML) applications for a range of improvements. AI and ML have helped factories with machine maintenance while sensors and industrial IoT software enable close monitoring of machines and their lifecycles. The same also applies for manufacturing processes, where AI is used to improve production efficiency and to release products to market faster. Pepsi is one well-known example of AI-powered manufacturing, addressing issues ranging from predictive machine maintenance to improving the production line.

Product design, too, benefits from AI and ML applications, since product designers and engineers can take a futuristic approach to design, as in the case of Hyundai. The auto manufacturer’s planned Ultimate Mobility Vehicle leverages AI-powered software to design parts for prototypes of two types of vehicles.