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In the manufacturing context, data comes from different sources, from shop floor and IoT devices, to IT systems such as MES, ERP, and APS. The amount of data manufacturers possess is abundant. Yet, without a proper collection and processing procedure in the manufacturing industry, most of the data would go to waste, creating a huge loss for growth opportunities.
Thankfully, with the rise of Industry 4.0, the increasing adoption of digitalization and smart manufacturing technologies, manufacturers today recognize the immense value of their data. However, acknowledging and being able to utilize the resources are two different things, and the latter, most often than not, still remains a challenge in the manufacturing industry. Lack of appropriate tools, involving risks with data security, reluctance to adopting new technologies, etc. are some of the common challenges in the way to digitalizing one’s manufacturing process.
The “Manufacturing Digitalization Roadmap” guide discusses common restrictions that prevent manufacturers from transforming to digitalization, and how to overcome such challenges. Our goal is to provide fundamental knowledge on how you can start your digitalization journey, with confidence.
Welcome to take the first steps with us. Download our guide now!
Connected
Manufacturers need to identify is important for them to define and determine the specific data points that are relevant to their manufacturing operations and objectives. Then, with appropriate tools, collected data should be visualized, best in real-time and in a format that is easily understandable for everyone.
Predictive
With advanced analytics, root causes of breakdowns can be identified more easily with statistical modeling or causal analysis techniques to determine the factors contributing to breakdown events. Understanding the causes and effects of their equipment, manufacturers can utilize them more efficiently.
Prescriptive
This is the highest level of data analytics, and it can prepare manufacturers for challenges
ahead and anticipate problems even before they arise. With such capabilities, prescriptive analytics will not only innovate manufacturing process but also decision-making in different parts of the business
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