As Heraclitus said, change is the only thing constant in life.  In the context of manufacturing it seems that there is almost a prescribed course—a road map with regularly spaced forks, one always leading to growth and prosperity, requiring change, and the other to stagnation resulting from fear of change, i.e., doing nothing and hoping that the definition of insanity is just a myth.

The most recent fork is the road to automation, the industrial Internet of Things, smart machines, smart factories, human machine interfaces, interfacing with learning machines, no less.  Is your head exploding yet?  It doesn’t have to, and it’s only complicated for those that have to dive deep into the weeds to make it all work right, the developers and integrators.  For manufacturing leadership, technology is just a component of strategic planning, a means to fulfill the vision, goals and objectives that lead to further growth.

A Look at the Industrial Generations

One of the labels assigned to this emerging manufacturing generation is Industry 4.0, the high-tech explosion that has a growth rate limited only by the users’ understanding, which includes a limited technical workforce.  Each preceding generation encountered similar obstacles.  The American Production and Inventory Control Society (APICS) contributed to the following definitions for these generations.

Industry 1.0:  In the 1800s, water- and steam-powered machines were developed to aid workers.

 Industry 2.0:  Starting with the 20th century, electricity became the primary source of power.  Mass production replaced craftsmanship, for the most part.  Just-in-time and lean manufacturing principles further refined the way in which manufacturing companies could improve their quality and output.

Industry 3.0:  In the last few decades of the 20th century, the invention and manufacture of electronic devices, such as the transistor and, later, integrated circuit chips, made it possible to more fully automate individual machines to supplement or replace operators. This period also spawned the development of software systems to capitalize on the electronic hardware. Integrated systems, such as material requirements planning, were superseded by enterprise resources planning tools that enabled humans to plan, schedule and track product flows through the factory.

Industry 4.0:  In the 21st century, Industry 4.0 connects the internet of things (IOT) with manufacturing techniques to enable systems to share information, analyze it and use it to guide intelligent actions. It also incorporates cutting-edge technologies including additive manufacturing, robotics, artificial intelligence and other cognitive technologies, advanced materials, and augmented reality.

Smart Factories Require Smart Planning

The obstacles governing the pace of adoption of technology might actually be good news for right now because adopting new manufacturing technologies cannot, and should not, match the pace of development.  And if you try, you may need to reflect on the end-game, that is, is automation the objective, or are improvements in critical processes that are aligned with organizational goals, growth really, your motivation?

According to a recent McKinsey study, since 2014, more than 80% of companies globally have made some form of investment in ‘digitalization’ – adopting digital technology to change business models, become more flexible and drive revenue.  However, less than 25% of these businesses have achieved topline growth as a result.  Let’s look at two major disconnects.

1. Automating Waste

One significant and all too common reason for not realizing the benefits, that the automation prophets and purveyors promise, is the lack of a sound strategy.  And that does not mean creating a schedule for acquisition and implementation of the latest technologies.   If you pardon the metaphor, a sound strategy involves preparing the road bed before laying down the technology. 

First and foremost you need to heed the wisdom of Peter Drucker:  There is nothing so useless as doing efficiently that which should not be done at all.  To more appropriately paraphrase:  There is nothing so useless as automating that which should not be done at all.  It’s much less costly and complex if outdated processes, or necessary processes bloated with wasteful activities are not automated.  As a colleague of mine reminds us, if you are doing the wrong things, automation will allow you to do the wrong things much faster. 

2. Metrics and Measurements: Too many, Too Few, and Wrong

To those of you familiar with Key Performance Indicators (KPIs), they are simply measures that most accurately reflect progress toward stated objectives.  To really make these measures useful they must be communicated in as close to real time as possible, and be actionable.  They must be the fuel for on-the-fly adjustments and decisions that keep you in the game to the end, rather than accumulating and publishing them after-the-fact, such as in end-of-period reporting.  This is the “best practice” of managing in real time.  And this practice should be established before automating.

Some final statistics extracted from the McKinsey Study that should be considered are:

• Process automation resulting from technology investments yields 2 percent productivity gains.  These are the types of projects where technology is used to make old, tired, broken processes run faster.
• Process improvements prior to automation yields 8 percent in productivity gains.
• When done together, i.e., improving the processes (eliminate waste and incorporate best practices) and then automating, yields 20 percent in productivity gains.

Smart factories begin with sound continuous improvement strategies and waste elimination.  Tools such as value stream and process mapping need to be performed to fully understand your processes and to optimize process targets for automation.

Automation Time

Finally, once the key processes supporting the enterprise vision, goals and objectives are identified, improved, and the appropriate key performance indicators are in place and communicated in real time, gaps in performance can be easily identified and opportunities for automating should be pursued.  At this point a whole new strategy must be developed, often with outside technical assistance.

Whatever the pursuit, there should always be a compelling business case for automation, i.e., return on investment, which can be daunting to identify, but still easier since you’ve accomplished the pre-requisites discussed here.

There may actually be immediate opportunities to benefit from these new technologies.  Why wait if they are low risk but provide easily measured and significant benefits?  One example is the collaborative robot, or Cobot.   Get on your favorite search engine and read up on them.  They’re here, they’re safe, reasonably priced, easy to program and ready to jump in to perform repetitive tasks, e.g., pick-and-place, assembly and hand-offs.  In many cases these are tasks that humans don’t want to perform -- repetitive, mind-numbing and possibly unsafe.  They also provide a nice introduction to the benefits of automation to your factory workforce.