The 7 Biggest Mistakes Manufacturers Make

whitePaper | August 31, 2022

The business case for collaboration and cross-functional transformation Faced with significant and ongoing disruption in the industry, manufacturing companies have known for years that digital transformation is essential to maintain a competitive edge. COVID-19 has only accelerated the need for digital transformation. The pandemic has disrupted supply chains, created an increasingly distributed and remote workforce, caused significant changes in demand, and increased the challenges of providing field service. To address these changes, manufacturing companies have accelerated their investments in digitization. According to McKinsey, advances in this area are now ahead of schedule by three to four years.1

whitePaper | August 1, 2022

One of the most important decisions that an asset-intensive enterprise must make is how to manage and care for its assets (i.e. equipment, buildings, plants and machinery). This is a decision that affects everyone in the organization, from the plant operators, to the engineers and all the way to executives in the C-suite. The solution will be different depending on the needs of the business and how each uses its assets.

whitePaper | October 23, 2021

Artificial Intelligence (AI) will increase the level of intelligence in the manufacturing industry by promoting, inter alia, the matching of production and demand, improving quality inspection, increasing product yield, reducing product failure rates, and improving production efficiency.1 While the last decade of Industry 4.0 was determined by technology-driven innovation, the coming years will focus on data- and intelligence-driven innovation. In this perspective, AI is an enabler for the transition from smart factories towards intelligent factories with self-optimising and self-healing characteristics. While smart factories are capable of applying previously acquired knowledge, intelligent factories will be able to autonomously acquire new knowledge and apply it for self-optimisation purposes.

whitePaper | January 11, 2022

While the technological maturity of AM has been demonstrated in specific industries, individual firms still struggle with its adoption and implementation at industrial scale. Companies underestimate the extent to which the adoption of AM is first and foremost a learning process that involves the entire value chain and requires specific AM expertise that needs to be acquired. Throughout this learning process, a wide range of challenges may hinder the progress and success of implementation.

whitePaper | August 17, 2022

The conversion brought forth by digital transformation and advanced technologies has made a tremendous impact on the way manufacturers process and manage their organizations. While the strategies of agile and modern management systems, specifically quality management, are the result of digital conversion, there is still limited understanding and unclear identification in this new era of quality assurance impact. With the development of digital methodologies, the classical system of operating businesses has been disrupted. As a result, many organizations are in the process of reacting to digitization by utilizing enhanced business platforms and rebuilding the waterfall approach to the agile approach

whitePaper | August 1, 2022

The story of manufacturing is one of constant technological change and evolution. It is also a story with a sweeping geopolitical arc from the industrial revolution in 19th century Britain to modern day China accounting for nearly 30% of the world’s manufacturing1 . The march of the machines is relentless and for large portions of society, alarming. Today’s technology is even imbued with the ability to learn – Blake Lemoine, a software engineer at Google, believes a chatbot his firm has created is capable of conscious thought2.