Manufacturing Inequality

By Oliver Perez, Ph.D, Director, Manufacturing Process Technology, BD

Oliver Perez, Ph.D, Director, Manufacturing Process Technology, BD

How do you make an economy and one of its most important drivers i.e. manufacturing, work for everybody in this globalized technological world when the transformation of raw materials into useful, appealing finish goods is constantly reinvented with innovative technologies?

We know the skills suitable for the factory of the future, thanks to the daily assault of articles and TV commercials talking about artificial intelligence, robotics and others. We make an effort to influence our kids on their college major selection because we understand that competing in the manufacturing world of the future will be a war for skilled labor. We give them tools to be in the pool of the chosen ones, the suitable ones, the useful ones. On this personal journey, we forget that companies are also competing to generate higher efficiencies; they compete to have the correct and best talent. This dynamic creates winners and losers increasing inequality with terrible consequences for the laggards, the technologically dumb companies, the incapable ones to attract talent, to understand the outside world millennials, and Gen Z are living.

This manufacturing narrow-mindedness is not from today, it started when managers and industrial leaders disregarded the benefits of Taylor principles, and got larger when the wave of Lean methodologies was considered costly to implement full of Japanese lingo with expensive consulting fees. Those short-sighted companies are fighting for survival pursuing for cheaper labor in unconceivable places. In contrast, visionary companies are looking ahead of the curve for process technologies to complement the benefits provided by continuous improvement methodologies.

But how do companies catch up? How manufacturing will adapt to the rise of disrupting technologies, how can companies surf the advanced manufacturing wave instead of being crashed by it?

The most important adjustment you need to do is to challenge the status quo, and change the glasses you use to look at your operation:

1. You have to look to your operation as continually producing data that vanish in the air, data that at this moment nobody cares to use for harvesting continuous improvements, for monitoring product quality in real time, to increase compliance or to take decisions when productivity goes south

2. You have to look to your operation as constantly wasting energy that doesn’t add value, energy is wasted when you see your production associates transporting material back and forth from warehouse to the production floor, lifting heavy loads or doing repetitive work

3. You have to look at your operation as repeatedly throwing away cognitive power when your assets aren’t smart, when you have long and complicated learning curves because nobody can find the latest revision of the paper based work instruction, or when you need to wait for the expert to travel across the continent to help solve a quality or maintenance issue

In order to harness digital data, energy and cognitive power, you have to invest in assets for your operation, develop talent, and adjust policies, in brief you need to have a manufacturing technology strategy. At this moment literature maybe confusing with fancy words such cyber-physical elements or neuro-technological enhancements but to reduce manufacturing inequality you have to start with two transformations: digitalization and robotics.

Digitalization: Once you are confident that you can plug your production floor to the network without putting your other IT entities at risk then you can proceed to identify your manufacturing technology pain points. You have a digital pain point when:

• Internal and external data are coming from multiple sources and different platforms, critical assets across the operation are isolated requiring special skills to retrieve, and analyze their data

• Productivity, quality, and delivery metrics are impacted because data are shown sporadically. Nobody knows the pulse of the operation if data aren’t collected and processed on real time

• Compliance is an overhead eater, it constantly needs headcount and “paper engineers” to check on manufacturing records. Failure investigations are an adventure that involves skills on how to dig into mountains of paper records

• Subject matter experts are far away from the facility and resolution on ship holds, maintenance issues, and new product releases take more time than needed

• Excessive inventory buffers are killing the cash flow because suppliers aren’t trustable; there is no way to check their quality performance or production status. Supplier visibility is basically nonexistent

• Infrequent or rare product configurations with low volume production depend exclusively on the savoir-faire of a small number of associates, taking longer, impacting productivity with lower levels of quality

• Inability to trace back failing components to specific raw material lots makes it impossible to narrow the quantity of finish goods exposed with financial consequences

• Engineering change orders take weeks to be implemented because decision takers are absent, and geographically distant from each other. The engineer “document pusher” waits outside the reviewer/signer office for hours

All these manufacturing discomforts and more have been solved already with digital tools such as Manufacturing Execution Systems (MES), electronic kan-bans, e-supply, augmented reality, wireless andons, statistical process control, electronic change orders, etc.. There is no need to continue suffering.

Robotics: Once you removed non-value added activities, and standardized your process to make it stable, safer, and predictable as much as possible then and only then you can proceed to look for robotics pain points manifested as:

• Production associates performing a combination of repetitive task, and dexterity movements

• Material handlers transporting raw material from warehouse into the production lines

• Production associates performing a repetitive test

• A low cycle time operation split across multiple associates to balance the process

• Employeesmoving material in-and-out of warehouse locations to make production order kits

• Production associates performing a dangerous task

• Production associates piling up cardboard boxes with finish goods, i.e. completing a pallet

• Production associates reaching for bulky components beyond their range

• Production associates lifting or moving around heavy weights as part of their activities

• Material handlers moving finish goods from production floor to warehouse

All these manufacturing distresses and more can now be solved using robotics such as collaborative robots. These robots share the work environment in a safer way without need of excessive guarding. The injuries associated with repetitive lifting of loads are now alleviated with the use of exo-skeleton robots. The endless trips back and forth between production and warehouse are now automated using Autonomous Mobile Robots (AMR).

In conclusion, if you are beginning your journey because you are experiencing a large manufacturing inequality, don’t overcomplicate your manufacturing strategy with unproven technologies. It is better to start with a small digitalization or robotics project that fits your needs and impacts your metrics than deploying a complex and large scale transformation.