IT IS NOT SURPRISING THAT MORE AND MORE companies are investing in Industry 4.0 and for the right reasons. It offers them faster manufacturing procedures, better margins, lower costs, optimizing processes, connected data, decisions made based on data—the list is endless. However, multiple legacy systems can hinder fast progress and bring in its own set of challenges. How companies truly maximize the power of Artificial Intelligence, Machine Learning and data analytics - all combined with deep domain expertise will prove to be critical in the age of Industry 4.0.
Industry 4.0 is the ongoing automation advancement of traditional manufacturing and industrial practices, using modern smart technologies. When an organisation with an existing legacy infrastructure makes a key decision to improve a process or line, lean improvements are often the first step. This is an important first step to ensure additional automation and digitization of a recently improved process. Otherwise, automation and digitization will only produce more outdated outcomes faster. To embrace Industry 4.0, some companies feel the need to fully understand and design a comprehensive Industry 4.0 solution. This is noble but usually leads to analysis paralysis, over investment, and rework. Companies successful with Industry 4.0 improvements typically only have a basic appreciation of the basic technologies available and requisites in terms of digital minimum standards. These successful companies often just get started in a key process, line, or area and then grow and learn and accelerate from there.
この記事は Manufacturing Today の January 2021 版に掲載されています。
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この記事は Manufacturing Today の January 2021 版に掲載されています。
7 日間の Magzter GOLD 無料トライアルを開始して、何千もの厳選されたプレミアム ストーリー、9,000 以上の雑誌や新聞にアクセスしてください。
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