Data is everything when it comes to manufacturing and is the key to tracking and improving production levels and performance. At Arcstone, we believe that data visibility and traceability is central to any manufacturer's first foray into digital transformation, and is the very core of how our solutions have been built.
The next step is using that data and transforming it through useful analysis and tracking for making the difficult decisions on your factory floor.
Turning the Key – The Value of Data
Industry 4.0 and Digitalization are no longer extraordinary terms reserved for technical experts and new age innovators. The manufacturing industry is no stranger now, having been through several revolutions of its own and with Industry 4.0 concepts being in the field for over 11 years. The core of it all in this Fourth Industrial Revolution? Data.
All industries are unique in their own fields, but all require data to operate daily. However, the disconnect exists between the collection of data and utilizing it effectively. Paper and excel based data won't be sufficient...
“Companies are still struggling to get data at their fingertips to make the first operational use of it, setting up this data foundation is first and foremost in the digitalization journey.”
Core Problems
Manufacturers now have the capability to capture vast volumes of data – Production, Machinery, Equipment, data et cetera. Despite the volume, the industry lags behind many others in terms of data management and automating tasks. The data in its raw form has tremendous value visualization and operational value, however, the gap still remains if the data isn’t fully utilized for further improvement and efficiency gains.
The first issue preventing the next expansion of data utilization is lack of skills and training of the current workforce. Insufficient training in modern software and solutions, coupled with a traditional mentality towards methodologies and operations, has translated into slow-moving digital transitions.
The second issue is siloed data. Arising from complex equipment, software dependency or just purely legacy issues, hundreds of data points per facility can be “trapped”. The data points may also be in constant flux due to changing inputs and collection requirements.
"Data integration and the proper setup of data lakes and unified name spaces is the next generation of data infrastructure needed for maximizing the value of data."
What’s the Best Practice then?
1. Incremental value use cases as data matures
Don’t jump for the exceptional use cases of data first (AI/ML/etc.). Use data at its fundamental stage for alerts, notifications and real-time efficiency first.
2. Inhouse Training & Hiring
Train internal staff to be data savvy and bring in data experts to help maximize the value of data within the organization. (Check out our education program for more related to training programs).
3. Algorithms, predictive analytics, and automation as a last step
Save the complexity towards the end when existing real-time data is maximized for operational purposes. This ensures manufacturers don’t over spec or overspend on efforts that may be ahead of their current data infrastructure/architecture capabilities.
Finding the “Golden Batch” of Solutions
Data definitely makes it better! Arcstone has worked to develop a powerful and scalable suite of solutions over the years, focusing on problem-resolution on a modular level, as individual manufacturers tend to face issues and barriers unique to their business or sub-industry. Our solutions are wholly integrative, software and hardware-agnostic, designed for manufacturers who want the most out of their data.
We also work closely with our network of partners and team of experts work closely together to provide for the needs of the industry, understanding that the job at hand requires more than just a singular solution.
Contact Us:
See how Arcstone’s Digital Manufacturing Solutions can unlock the most of your data and schedule your demo today! Visit us at www.arcstone.co or drop us an enquiry at contact@arcstone.co
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