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Empowering manufacturing with Advanced Analytics
EM - Efficient Manufacturing
|Efficient Manufacturing - Feb 2024
Data analytics is a crucial element in the digital transformation of various industries, with manufacturing being no exception. This article outlines how tools for manufacturing analytics can effectively identify upcoming trends, enabling manufacturers to proactively strategise production, equipment maintenance, quality control, and raw material procurement.

Manufacturing analytics refers to using data generated from machines, operations, and systems to manage and optimise production, including maintenance, quality, and planning.
Manufacturers have always used data to improve the efficiency of their production process. But today, this has changed significantly in how data is collected.
While many companies still rely on fragmented, traditional methods to manually check and record factors and write down machine operation and maintenance histories, unfortunately, these methods are not only highly prone to human errors but are also time-consuming and often biassed, making them inefficient in generating quality insight for accurate decision-making.
However, as the manufacturing industry undergoes a digital transformation, devices are connected to reduce the labour associated with manual documentation. Automated machine data collection mechanisms are propelling the next generation of manufacturing analytics to unlock the most accurate forecast based on a plethora of advanced use cases ranging from straightforward monitoring and diagnostics to predictive maintenance and the aftermath of automation.
In new-gen manufacturing analytics, data that records events can be utilised to enhance equipment performance, drive process improvement, save costs on production, and minimise human errors. The tool provides reliable information that reveals accurate equipment conditions and trends in production.
Types of Marketing Analytics
Manufacturing analytics is a collection of different processes that provide insights businesses can leverage to implement data-driven decisions. Here are the four types of marketing analytics that marketing businesses can apply to their company's pipeline:
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