New product introduction (NPI) is an essential part of bringing a product from concept to its final form. The goals of NPI often include reducing waste, speeding up production, and saving money. However, achieving these goals is not always easy.
Only about 53% of manufacturers currently use big data analytics. The insight provided by data processing can lead to more agile NPI processes, which could create a giant competitive advantage for your business.
What Is a New Product Introduction (NPI)?
NPI is the process of taking an idea, developing it, and getting it to market. An NPI process is typically…
Production ramp-up is a necessary practice in the manufacturing industry. Manufacturers constantly strive to achieve faster time to market to remain competitive. However, ramping up production involves additional obstacles, including the need to balance cost, volume, and quality.
Creating a digital transformation roadmap can help deliver cost-effectiveness and increased volume through more agile manufacturing practices. Here is a closer look at how creating a digital transformation roadmap for product ramp-up can assist your manufacturing processes.
What Is a Digital Transformation Roadmap?
A digital transformation roadmap lies the groundwork for implementing the latest digital manufacturing solutions. Artificial intelligence (AI) and machine…
One of the challenges of bringing a project to light is getting approval from the C-suite. You cannot move forward with your idea until you get C-level buy-in, which increases the risk of your competitors rolling out comparable projects before your organisation.
Consider using the following recommendations to get your next innovation project approved and help create additional tangible value for your organisation.
Understand What C-Level Executives Care About
Selling a product requires you to understand the needs and interests of your target customer. You should use the same approach to successfully pitch your project to decision-makers. …
In the age of big data, the need for data-sharing solutions has become increasingly apparent. Artificial intelligence and machine learning technologies provide endless potential for the manufacturing industry. However, these technologies are limited by the amount of data that they can access.
Manufacturing processes already frequently involve several stakeholders working together to meet tighter timelines and rising quality requirements. Each of these stakeholders has separate pools of big data, yet the data remains isolated.
Bringing together more data can help remove previously hidden bottlenecks and increase manufacturing output. Of course, data sharing also requires trust and honesty between stakeholders. …
Sensors are a critical part of smart data collection in the manufacturing sector. A smart sensor can collect data in real-time to help artificial intelligence (AI) software and employees make smarter decisions. To increase the effectiveness of your AI and machine learning (ML) solutions, explore the value of sensors on the production line.
What Data Do Sensors Collect?
Sensors can collect data from machines and equipment or the environment. A smart sensor typically contains a microprocessor and communication capabilities for relaying data to a central system, such as an artificial intelligence (AI) system.
Artificial intelligence (AI) has the potential to revolutionise the manufacturing sector. AI helps manufacturers reduce waste and develop more efficient processes. However, AI is unlikely to provide satisfactory outcomes without a focus on the human end users.
Here is a closer look at the importance of a human-centred AI approach in manufacturing.
What Is Human-Centred AI?
A human-centred design involves the development of AI systems that collaborate with humans. With a human-centred approach, AI systems are set up on the existing data and human input is included where either data is not available or more creative problem-solving skills are needed…
Manufacturing is going through the fourth industrial revolution as many are using large-scale data analysis, artificial intelligence, machine learning, and the Internet of things (IoT) to dramatically improve efficiency. The following information explores the impact of these initiatives on the manufacturing industry and the business processes that often have not changed for decades.
Big data and data analytics
With increasing complexity of Industry 4.0, data-based decision making has become the new norm in manufacturing. Traditionally it has been sufficient to rely on engineer’s knowledge and maintaining buffers to handle fluctuations in production. …
Artificial intelligence (AI) technology has progressed rapidly in the past decade. AI algorithms can process data and make decisions in real-time, achieving a level of decision-making that typically requires human input.
Manufacturers began incorporating AI in the 1960s. However, early AI technologies essentially provided automation and could not make complex decisions.
Manufacturers now use AI for a wide range of applications. More companies are starting to discover the value of industrial artificial intelligence. About 63% of manufacturers are already reporting revenue increases from AI adoption.
Here is a closer look at some of the most impressive ways to incorporate AI…
Digital transformation is revolutionising every aspect of the way manufacturers cater the needs of the consumers. Robotics are replacing manual labour and artificial intelligence is helping companies make smarter decisions. The manufacturing processes of the 20th century are outdated and inefficient. Compared to AI-optimised facilities, older assembly lines experience increased downtime, waste, accidents, defects, and fraud. Here is a closer look at the importance and industry adoption of machine learning and digitisation in manufacturing.
What Is Digital Transformation?
Digital transformation refers to the implementation of digital technologies to replace manual labour or analogue processes. Digital transformation is pushing through in…
Manufacturing methods continue to evolve. Companies that implement the latest technologies are enjoying increased efficiency, thanks to reduced downtime, fewer defects, and streamlined processes. The advantages come from an interconnected manufacturing facility with access to advanced monitoring and analytics. Connecting, automating, tracking, and analysing are now key practises for successful manufacturing.
Connecting New and Legacy Equipment
The latest innovations in machine learning (ML), artificial intelligence (AI), and automation rely on interconnected devices and equipment. Connected manufacturing equipment can communicate with central data acquisition systems and human-machine interfaces (HMI).
Some of the newest manufacturing equipment features electronic components for monitoring and…