“Nearly 75% of midsize business owners say they plan to expand their businesses, and the vast majority (90%) are implementing digital strategies to better achieve that growth”.

This was a major finding of a recent Industry Week White Paper, which went on to say that “to achieve these numbers and potentially outperform competitors, manufacturers need to focus on supply chain excellence”.

The white paper identified 3 best practices for achieving this supply chain excellence:

• Automation and AI for agility

• Efficient operations for resiliency

• Increased visibility for customer centricity

Automation and AI for agility

In today’s business environment the pace of change, customer expectations, and supply chain complexity are at never-before-seen levels. And companies are looking to address these challenges in the face of growing regulations, sustainability mandates and employee shortages.

To keep up with the pace of these challenges and still grow, many companies are looking to advanced automation and AI And to do so.  

Efficient operations for resiliency

Resiliency has been top of mind for companies of all sizes since the start of the pandemic in 2020. And it seems like we have had business disruption after disruption ever since. So much so that permacrisis was the Colins Dictionary word of the year for 2022.

Companies have prioritized investments in risk-resiliency strategies such as identifying alternate sourcing strategies, driving inventory optimization processes, improving visibility and collaboration with business partners, and digitizing end to end processes.

Increased visibility for customer centricity

The white paper references a recent report that highlighted that “companies are struggling to maintain the quality of their products and services while at the same time increasing the speed of interactions with customers”. The study stated that Real-time responsiveness is their top barrier to supply chain success, cited by 40% of respondents, followed by meeting customer demands on time (34%).

It is clear from the paper that the more “customer centric” a company becomes, the better they are at meeting their customers’ requirements.

It is also clear that regardless of the business challenge, increased visibility and transparency of the situation enables you to identify and even predict risks and opportunities and be in a position to respond in a timely manner. 

To learn more, download the Industry Week White Paper – Three Milestones That Put Midsize Manufacturers on the Path to Supply Chain Excellence

A year ago I began this series of articles describing how a 4^th industrial era (I4) automation system is built. We have now arrived at the peak of the pyramid with the Enterprise Resource Planning (ERP) system, which is level 4. As a reminder, these are the levels of an industrial automation systems:

• Level 0: Instrumentation (connecting automation to the process with valves, sensors, etc)
• Level 1: Digitalization (wiring instrumentation to devices for data acquisition and/or control, which may include logic for loops, interlocks, and alarms)
• Level 2: Supervisory (a deterministic network for operator interface, engineering, historical data, and applications such as advanced control and data analytics)
• Level 3: MES (the bridge between the operational technology (OT) at the lower levels to the information technology (IT) at the upper level)
• Level 4: ERP (the financial system for the enterprise)

If a system is built as described in the prior articles, an ERP can be placed on top of a good foundation for delivering the benefits of I4. These include:

• Visibility through the enterprise of realtime operating conditions
• This visibility makes it possible to see the financial impact of operational concerns
• Since this is now a realtime connection, decisions can be made in a timely manner to mitigate financial losses when operational concerns arise
• With a timely connection and established cause and effects relationships, it provides the basis for automation/optimization at the enterprise scale

To make this more tangible, imagine a paper machine that has a sudden mechanical failure. Prior to I4, the mill scrambles to get production going again and the enterprise may be unaware of the impact. It could mean delays in fulfilling orders. It could mean the mill is unaware of resources within their enterprise, such as other mills, that may be able to provide equipment quickly at low cost. It may mean that production that could be shifted to another mill isn’t because the enterprise cannot coordinate this in realtime. This I3 scenario could involve lots of emails and phone calls that create confusion and frustration.

In I4, ERP can be the dashboard that mitigates this condition. ERP can be aware of realtime key performance indicators (KPI) such as Overall Equipment Efficiency (OEE). Based on OEE, critical orders can be shifted to mills that have the capacity for the grades required. Resources that can help the mill can be identified and quickly deployed. 

In the longer term, an I4 connected ERP greatly facilitates future planning with much less effort and greater accuracy than relying on compilations of written documents and spreadsheets.   

For approximately the last decade, many of us have heard that we need to digitize industry. That comes as a surprise, since for the last 50 years or more industry has been digital. What are they talking about?

It is at this stage, the Manufacturing Execution System (MES), that we finally see what these people have been talking about. 

The companies that reach an I4 level of automation will be the high performers, and those that don’t will find it challenging to compete. Now that you see how to make this happen, it is up to the reader to make it a reality.

As this publication continues in its sixth year, the drumbeat has been steady...more and more electronic machine learning supplants human interaction. In this month's issue, Pat Dixon brilliantly shows us the phases while Richard Howells provides vision for what is to come.

Automation was first, the automation of routine tasks formerly done by humans. Thinks of floors and floors of people with monstrous desktop calculators at insurance companies or scheduling departments in paper mills with tracks around the wall loaded with snipets of paper representing scheduled orders. These tasks ended up buried in computer memories long ago as they became automated.

Today we are talking about AI--Artificial Intelligence. It is a concept with great promise but also great questions about when it will be significantly implemented to make a noticeable difference. Elon Musk says AI will surpass human intelligence next year, others say not so fast. Who knows?

The unsung hero in all these machinations, however, is the never ending, precipitous drop in computer memory costs. The unrealized potential is in developing a similar savings in energy consumption by computing devices.

Computer energy consumption appears to this old engineer to be the barrier to overcome for widespread adoption of AI, and no one is talking about it in the popular press.

The Internet of Things (IoT) technology is becoming increasingly common in heavy industries like construction and warehousing. While human-centered IoT solutions are emerging, machine-focused systems are among the most promising of these use cases. Overhead handling equipment, in particular, can gain a lot from IoT integration.

The Smart Factory system has highlighted the recent transformations in the manufacturing industry. The talk about the concept is set to be even more pronounced as players jostle for space in the increasingly interconnected and intelligent manufacturing environment.

Industry 4.0 has been a bedrock of innovation for at least the last decade. Now, as generative AI, advanced Machine Learning, and modelling algorithms become more accessible with “off-the-shelf” technologies, questions are being raised about the value – and risks – artificial intelligence might bring to the sector.

In today’s tech-driven era, the demand for skilled professionals in the Internet of Things (IoT) sector is soaring. This industry, permeating sectors like manufacturing and healthcare, faces a significant skills gap. This gap extends beyond technical aspects, including the electrical and computer engineering degree required to oversee the intricate IoT landscape. Enter online STEM and business programs. These initiatives are critical, offering professionals the chance to enhance their skills and career prospects.