It’s no secret that technology is a heavy focus for today’s manufacturers. Unfortunately, many manufacturers often focus on technology as an end, when in reality, technology is a means to achieving better business outcomes.
The promise of the benefits that can be reaped from big data and predictive analytics through access to machine and operator data is compelling enough for most manufacturers to seriously direct their IT and OT departments to look into ways to enable such machine and operator data acquisition. Indeed, being able to optimize overall equipment effectiveness or OEE in terms of equipment availability, performance and quality of produced items by the equipment directly affects manufacturers’ bottom lines.
The act of “putting out a fire” is associated with resolving an urgent problem. Afterward, we worry about the cause, the consequences, and what knowledge we can gain, or so we believe. Quite frequently, this next step is replaced by handling and putting out the next fire. The digital factory provides us the ability to prioritize quality “hot-spots” that require handling. However, in world-class organizations, we must ensure that we complete the additional step and do more than extinguish the flames.
People have begun describing their cloud systems as "the fog." I get the feeling the joke is based on actual events. Are we" venting" gases into the atmosphere with our data during this digital era just like we did during the industrial age? Is it possible to simply throw our data in the cloud and expect a software application to analyze and organize it when we need it? But first, we must begin with an understanding of what the cloud can and cannot do, as well as knowing what is required to make the cloud an effective strategy for storing data that is easily accessed.
Eliminating paper in manufacturing, also known as the Smart Factory or Industry 4.0, is just the first step of the digital revolution. There has been a significant transformation when we compare modern-day printed material to that of our ancestors’ early drawings of shapes, symbols, and pictures on cave walls. The next step of this advancement is more than just becoming ‘paperless.’ Transferring physical media into the digital domain, a crucial element of our digitalized Smart factory, provides a far more significant fundamental change. The future of ‘Paperless Manufacturing’ is much more than just eliminating paper from manufacturing.
The heart of the electronics factory is in its' machines. However, even the lines and factories with the smartest and most versatile machines rely on intelligent and consistent support received by the central processes to reach their maximum capability. The heart of the electronics factory is in its machines. However, even the lines and factories with the smartest and most versatile machines rely on intelligent and consistent support received by the central processes to reach their maximum capability.
The catalyst for the now long-awaited Industry 4.0 revolution is the introduction of the IPC CFX (Connected Factory Exchange) standard for IIoT. This standard now enables everyone in the industry to get involved, examine their processes or products and to fully benefit from the new IPC CFX-fueled Industrial IoT environment.
In order to improve productivity growth, it is critical that manufacturers strategically adopt factory-wide technology that actively promotes workforce efficiency. But which technology is worth the investment? To find out, let’s examine the top productivity pain points manufacturers are experiencing today.
The Cyber Physical System (CPS), Internet of Things (IoT) and Digital Twin are all central concepts in Industry 4.0, often used interchangeably in discussions about Industry 4.0 and smart manufacturing. Each refers to a representation of a piece of equipment in cyber space. Such representations are of central importance in Industry 4.0 and for smart manufacturing, since they provide access to real-time operational data of the represented equipment. Use of this data ranges from machine operational status and compiling important KPIs, like OEE, MTBF, MTBA, etc., to big data analytics and machine learning applications, such as predictive maintenance. It is therefore worthwhile to examine what each means and how they relate to each other.
More advanced technology equals higher workforce productivity—this is the simple equation that drives enterprise strategy for many manufacturing leaders. But technology and productivity do not always increase in direct correlation with one another. Instead, it is only by strategically investing in the right technology solutions that manufacturers can ensure effective productivity gains for their workforce.