Author – Tim Smith
As Industry 4.0 and IIoT continue to dominate the advancement of manufacturing, the results of exposure to such disruptive technologies can be mixed. The factors behind adoption can be varied and even extreme at times. The application of Industry 4.0 philosophy to a plant or enterprise, starts on the shop floor. There is no value in the data itself but in the interpretation and application of the information culminated in the data. The generation of new engineers, administrators, managers, and execs get it. The old guard struggles with it. Meeting additional demand by adding more machinery no longer works. A new machine must be justified by a committed demand. It requires real estate on the floor, it requires skilled labor and resources to run it. It requires ongoing operational costs to support it. Shop floors are littered with machinery which are only periodically used and are kept for the “Just in case” scenario. This approach is costly and inefficient at best. An industry 4.0 floor is a monitored, managed, dynamic environment where resources are leveraged and utilized to their maximum potential. As the old guard changes to the new breed of manufacturing technologists, digital transformation is the requirement to be profitable.
Industry leaders in Industry 4.0 like Mazak USA saw double digit efficiency gains years ago even with early adoption. In fact, Mazak USA is moving into the next renaissance in Industry 4.0, leveraging the technology for even more gains.
The challenge to adoption is the unknown. Most companies have a few technology blunders hidden in the closets. These skeletons are what the old guard point to whenever a new technologist tries to introduce enterprising and enabling new technologies such as Industry 4.0. What is strange is that these same old guard stalwarts who oppose the adoption of Industry 4.0 will buy new tooling technologies, new manufacturing technologies, new cutting fluid technologies, all because they bolt onto a machine they can touch. However, the approach to Industry 4.0 should be the same. Connect the machine and let it tell you what it is doing. Is it productive? Or is it not?
But to realize the promise of Industry 4.0 one must adopt it. 27% of manufacturers already started adoption in 2015 (https://www.accenture.com/t00010101T000000__w__/gb-en/_acnmedia/Accenture/Conversion-Assets/DotCom/Documents/Global/PDF/Dualpub_11/Accenture-Industrial-Internet-of-Things-Positioning-Paper-Report-2015.ashx) . The adoption of Industry 4.0 positively impacts many areas in manufacturing, from improvement to throughput of the plant, reduction in maintenance costs and firms can even reduce yield loss by up to 30% using AI-enabled yield enhancement systems. Automating quality tests with AI can increase defect detection accuracy by up to 90% when compared to humans (Machine Learning & A.I. Statistics & Trends by Mckinsey & Company)
Each day that a company allows to go by without pursuing Industry 4.0 initiatives costs the company production dollars. Waiting costs money.
The average plant in North America is grossly inefficient with the majority showing 55% or less. This value is historically accurate based on the last ten years of adoption history. That means that basically 27 minutes out of every production hour is wasted. When an hourly burdened production cost of $95/hour (average estimated burdened hourly production cost. Your cost may differ) is applied to the lost minutes that equates to a cost of $42.75 per hour per machine of lost production time. As an example, for a shop of 10 machines, that is $6,840 per day (based on 16 scheduled hours) of lost production time. That would mean that every week you wait costs you $34,200 and every month that slips by costs you $148,086 in lost production time.
The typical shop will see efficiency improvements starting at 10% by employing Industry 4.0 and will enjoy efficiency improvements closer to 30 or 40%. If we only apply the minimum expected improvement of 10%, that will gain back 3.3 minutes or $5.22 per machine, per hour recovered. That would mean that if the system were in place you would have recovered $18,082 of lost production time on ten machines for every month. Triple that amount for a typical customer experiencing 30% to 40%. (https://www.accenture.com/us-en/insight-industrial-smart-production) The full shop deployment of a manufacturing operations management system like MERLIN Tempus would have been paid for long ago and you would be reaping the return on your investment.
The investment per machine to employ Industry 4.0 is nominal. The impact to the floor is minimal and controlled. Vendors like Memex have productized the adoption of Industry 4.0 over the last ten years eliminating guesswork and risk. Greater efficiencies from I4.0 (Industry 4.0) can even drive reshoring initiatives. (Journal of World Business,Volume 54, Issue 6, December 2019, 101017, https://doi.org/10.1016/j.jwb.2019.101017) states that I4.0 supports backshoring (European term for reshoring) because it provides a higher productivity and flexibility which offers an incentive for firms to locate production close to their…customers. Even the automotive industry is expected to show a significant savings by adopting I4.0 initiatives of over $28 Billion between 2016 and 2020 (Source: https://themarketmogul.com/industry-4-0-next-industrial-revolution/)
In the end, waiting costs you over $600 in lost production per machine per day, minimum. Of course, this is a general application across all machines. Once you have a solution in place you may find much larger production losses in specific cells, lines, or value streams. The paradigm shift to digital manufacturing could see an adoption rate as high as 72% throughout manufacturing. (Source: https://www.forbes.com/sites/louiscolumbus/2016/08/07/industry-4-0-is-enabling-a-new-era-of-manufacturing-intelligence-and-analytics/#b0b0f877ad90) In fact a German survey reported 91% of respondents are investing in digital factories, but only 6% consider their factories to be fully digitized.
You cannot wait because the cost of waiting is too high.