2-Keys to Avoid Dot-com bubble in Industrial Internet Brilliant Factory

1. Introduction:

We all remember suffering through the early Dot-com bubble between 1997 and 2001. Back when the potential of the “Internet for E-commerce” was beginning to emerge.

In those beginnings we watched as poorly-conceived E-commerce sites with useless applications tried to convince us that we were going to miss the “Next Generation of Commerce-boat” if we didn’t jump on board NOW!

Does anyone remember Boo.com?

This frenzied rush to the internet, fueled by marketing department hype ended up wasting billions of dollars, incredible amounts of time and dashed countless people’s careers.

Ending in one of the biggest stock market crashes of all times when the NASDAQ fell more than 75% and lost nearly $5 trillion in market value.

A failure that we are now just recovering from… some fifteen years later.

If we are not careful, the “Industrial Internet” (aka Internet 4.0, Industrial Internet of Things, IIoT) could follow the same path of devastating financial loss and career derailment.

Not because the disruptive technologies at the heart of the Industrial Internet (such as Smart Connect Devices and Big Data Analytics) are not ready for prime time, because they are close. But rather because of the poorly-conceived, useless applications that these technologies are first being applied to disrupt.

Does anyone really need their Barbeque Grill to text them when the propane is low?

If you look at the current landscape of early Industrial Internet “Proof of Concepts” and “Pilot-projects”, focused on factory floor applications, they too seem to be littered with poorly-conceived use cases (fueled with marketing hype) trying to convince us that we will miss the “Next Generation Industry-boat” if we didn’t jump on board NOW!

              Giving one the feeling that we are starting to refill the Dot-com bubble of the late 1990’s.

 The rest of this article strives to direct our attention towards the highest value Industrial Internet factory floor applications and use-cases as they apply to discrete part and build to order design and manufacturing processes:

Products and Processes that are found within industry verticals such as Aerospace & Aviation, Military & Defense, Power & Water, Medical Devices, Transportation, Energy, Machine Design and Consumer Products Design.

If we focus the Internet’s disruptive technology on the right factory floor problems, we won’t relive the Dot-com failures of the late 1990’s.

 2. Making the Main Thing..."The Main Thing" on the Factory Floor:

If you spend enough time with leading discrete part and build to order engineers you will discover that the majority of their problems (design, manufacturing, customer satisfaction and service) come from a relatively small handful of Product and Design Requirements (their “Main Things”).

These requirements are known as Key Characteristics (KCs) and are:

•  Critical for the functionality of the final product’s performance, reliability, quality and safety.
• Typically cause the most variation in the final product if not manufactured to specification.
• Should be closely tracked when and where they are created in the manufacturing process and
• Should be reacted to quickly if they deviate from specification during the manufacturing process.

Similarly, discrete part and build to order manufactures will tell you that their “Main Things” are a handful of Business and Process Requirements (metrics) used to evaluate factors that are critical to the profitable production of those product requirements.

These Process Requirements are known as Key Performance Indicators (KPIs) and are things such as:

• The ideal time to produce a single unit (Takt Time).
• The number of tasks performed that were unplanned or took more time than expected (Schedule Variances).
• The value (cost) of partially finished goods waiting for completion and eventual sale (Work in Process Inventory).

It follows that we should direct our attentions and the power of the Industrial Internet’s disruptive Smart Connect Technologies and Big Data Analytics towards automating and optimizing the way Key Design Characteristics (KCs) and Key Performance Indicators (KPIs) drive our discrete part and build to order design and manufacturing processes.

By doing so we will dramatically improve the major product problems facing design engineering while simultaneously optimizing those production factors critical to the profitable manufacturing of those products.

Thus creating a New Brilliant Factory from our Industrial Internet technologies…which track and optimize the “The Main Things” …KCs and KPIs.

3. Weaving KCs & KPIs into Brilliant Factory Fabric: The Digital Thread & Twin

Our New Brilliant Factory Product Design and Manufacturing Processes can be best optimized when we identify, track, monitor, analyze and correct our Product Key Characteristics and the Process Key Performance Indicators that manufacture those Key Characteristics.

This can be achieved when we build awareness of KCs and KPIs into the fundamental pillars onto which the Industrial Internet and our New Brilliant Factory will be built. Namely the “Digital Thread” and the “Digital Twin”.

Where the Digital Thread is defined as two (2) unique but related threads:

1) The As Designed Product Digital Thread for the desired Product which will include:

• The designs of the parts and assemblies created by 3D CAD Systems.
• The identification (by design engineering) of the Key Design Characteristics (KCs) for those parts and assemblies using Model Based Definition (MBD) practices and
• Their corresponding Engineering Bills of Materials (eBOMs) stored within PLM Databases.

2) The As Planned Process Digital Thread for the Smart Connected Manufacturing Processes required to make the Product which will include:

• The processes required (planned) to manufacture the parts and assemblies
1. Such as process plans, work instructions, assembly instructions
2. Which focus attention on the Key Design Characteristics,
3. Created by Model Based Enterprise (MBE) practices and MES Systems.
• The identification (by manufacturing operations) of the Key Performance Indicators (KPIs) for the manufacturing processes and
• Their corresponding Manufacturing Bills of Materials (mBOMs) stored within ERP Databases.

These two (2) Digital Threads act like the “DNA-scaffoldings” onto which the Smart Connected Manufacturing Processes will stream their real-time manufacturing data, as built product dimensions, deviations from specifications, quality results and big data analytics and corrective guidance.

And where the Digital Twin is defined as these two (2) corresponding Data Twins:

1) The As Built Product Digital Twin generated from the actually manufactured dimensions and deviation from tolerances for the Key Characteristics produced by the Smart Connected Manufacturing Processes, “instrumented” (added) into the As Designed Product Digital Thread and 

2) The As Manufactured Processes Digital Twin generated from the actually achieved Key Performance Indicators from the actual Smart Connected Manufacturing processes, “instrumented” (added) into the As Planned Process Digital Thread.

Said another way:

• The As Designed Product Digital Thread + Actual Measured Key Characteristics (from the Physical Product) = As Built Product Digital Twin

(See Figure 1 below).  

• The As Planned Process Digital Thread + Actual Achieved Key Performance Indicators from the Physical Processes that created the Key Characteristics) = As Manufactured Process Digital Twin

(See Figure 2 below).

When we focus our New Brilliant Factory Digital Threads and Digital Twins on Producing Key Characteristics and optimizing our Key Performance Indicators, we are putting the disruptive technology of the Industrial Internet, the Smart Connected Factory and Big Data Analytics on the most important aspects of our operation.

Thereby focusing our attention and disruptive technology on The Main Things.

4. Some Value Propositions for the New Brilliant Factory:

Our New Brilliant Factory which utilize the Industrial Internet’s Smart Connected Machines and Big Data Analytics to focus on tracking and optimizing Key Characteristics and Key Performance Indicators will drive the following value propositions:

• Design driven manufacturing allows for Product Key Characteristics (KC) to be closely monitored and controlled allowing for high quality, high reliability and high customer satisfaction part and assemblies to be consistently produced (“As Designed”).
• Real-time tracking of Key Performance Indicators (KPIs) improves factory efficiency and time to market by instantly sensing when the Smart Connected Factory is no longer performing (“As Planned”).
• Optimizing Throughput and minimizing Work in Process Inventories (WIP) Increased Profitability and time to market.
• Automated Manufacturing Process Setups and machine health monitoring reduces factory setup and down time and improves overall product time to market and competitiveness.
• In-context collaboration and reports reduces shop floor misunderstandings, scrap and rework expenses.
• Agile Manufacturing setup allows for quick response to economic trends and customer’s changing demands.
• Connectivity to Products in the Field improves Service Times, Customer Satisfaction and increases Customer Loyalty.

5. Some Important Use-cases for the New Brilliant Factory:

The value propositions identified above for our New Brilliant Factory can be most quickly achieved by focusing our attentions and the power of the Industrial Internet’s Smart Connected Machines and Big Data Analytics on the use cases listed below and potentially in the order listed below:

New Brilliant Factory Use cases:

1) Process and Resource Tracking and Routing

• Real-Time Machine Sensor Data Streaming into our Product and Process Digital Threads to create and update their real-time Digital Twins.
• RFID Factory resource tracking.
• Raw Material and WIP monitoring and corrective planning.
• Tooling, Fixtures, Gages tracking and assignment.

• Personnel (time on Task) tracking.

2) As Designed Product Digital Thread Key Characteristic (KC) Tracking

• Compare As Designed with As Built KCs.
• Quickly Respond to out of spec KCs by collaborating with Engineering.
• Add to the As Designed Product Digital Thread the final measured KC values creating/updating the As Built Product Digital Twin.

3) Process Digital Thread Key Performance Indicator (KPI) Tracking

• Compare As Planned with As Manufactured KPIs.
• Quickly Respond and recover from failing KPIs by collaborating with Operations & Logistics.
• Add to the As Planned Process Digital Thread the achieved KPI values creating/updating the As Manufactured Process Digital Twin.

4) Shop Floor Optimization

• Identify shop floor problems prioritized by Key Characteristics and Key Performance Indicators used to manufacture those Key Characteristics.
• Remove Bottle Necks and Optimize flow of material and resources, minimize WIP Inventory.
• Applied Theory of Constraints with Big Data Analytics from a KC and KPI perspective.

5) Design Driven Generative Manufacturing

• Create Generative Process Plans focused on the design Key Characteristics.
• Create Generative subtractive NC and additive 3D Printer Machine Tool paths focused on the design Key Characteristics.
• Create Generative Quality Plans focused on the design Key Characteristics.
• Implement Real-Time In-process Inspection.

6) Field Service and Remote Product Update

• Virtual analysis and stress testing of Product Digital Twin.
• Predictive maintenance and optimization using Big Data Analytics on the Product Digital Twin and the Process Digital Twin.
• Remote Deployment of updates, service packs and software patches to the Smart Connected Physical Product in the field.
• Automatic Update of Product Digital Twin to match the current state of the Product in the Field.

  6. Conclusions:

There is no reason why the early promises of the Industrial Internet and the New Brilliant Factory need to cause wailing and gnashing of teeth like the early Dot-com and E-Commerce failures we suffered through in the late 1990’s.

To prevent this from happening in Discrete Part and Build to Order Manufacturing industries we will need to implement Smart Connected Machines and Big Data Analytics on the right problems in the right order “The Main Things”.

The Industry Leaders in today’s discrete part manufacturing companies know that these Main Things are a focus on Key Characteristics (KCs) and Key Performance Indicators (KPIs).

By weaving KCs and KPIs into the fabric of the New Brilliant Factory and into the foundations created by the Digital Thread and Digital Twin, we will guarantee that the disruptive Industrial Internet technologies will achieve the promises we believe they can achieve and in the time frame we need them achieved…

…Which is NOW!

Your thoughts, comments, likes (dislikes) are welcome through LinkedIn or my email [email protected]

Thank you for your interest…

Chris Garcia

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Other recent Industrial Internet articles I have written and posted on LinkedIn

Getting the Manufacturing Fundamentals Right (written Oct 29th, 2015)

https://www.dhirubhai.net/pulse/new-industrial-internet-getting-manufacturing-right-garcia?trk=pulse_spock-articles

Manufacturing Killer Apps in the Industrial Internet (written Dec 30th, 2015)

https://www.dhirubhai.net/pulse/manufacturing-killer-apps-industrial-internet-garcia?trk=prof-post

and this article:

Two “Keys” will Unlock the Industrial Internet and the New Brilliant Factory (written March 11th, 2016)