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Live Product Innovation, Part 3: Process Industries, IoT, And A Recipe For Instant Change

John McNiff

In Part 1 of this series, we looked at how in-memory computing affects live product innovation. In Part 2, we explored the impact of the Internet of Things (IoT) and Big Data on smart connected products. In Part 3, we approach the topic from the perspective of process industries.

Digital this, connected that. Smart whatsits and intelligent doodahs. Those of us who talk about IoT are often reminded that not every manufacturer makes products per se. But IoT isn’t only about the addition of sensors to products. The principles of live product innovation are equally relevant to process manufacturing.

In fact, the “data refinery” offers the potential to manage the Internet of everything — including traditional Big Data sources in tight conjunction with business processes. If your products are food, packaged goods, or chemicals, the promises of live product insights are still compelling. It’s only the data sources and dimensions that are different.

Live and compliant

The complexity of regulatory compliance in process industries continues to grow — whether you’re talking about the U.S. Food and Drug Administration, the U.K. Food Standards Agency, trade embargoes, or hazardous substance management. And compliance isn’t getting any simpler to manage across jurisdictions and industry sectors.

What’s more, customers increasingly demand shortened delivery cycles and highly targeted or even personalized products. That means you can no longer wait till after you formulate a product and release a recipe to determine whether you can actually sell it. You need instant visibility, whether you’re talking about nutritional safe levels assigned by a particular region for food products or volumes of hazardous substances for supply and transit.

But that’s the advantage of live, compliant product innovation. It enables you to perform analytics on previously disconnected data. And it allows you to manage real-time embedded processes across previously disparate systems.

Product data is everywhere

In our last blog we explored the advantages of smart connected products — the ability to link everything from initial product concepts through downstream product delivery. Now let’s apply that to process manufacturing.

Let’s say you see two factors coming together for the SoySnak product you sell in North America and Asia. Your sales data shows that American consumers want 10Kg packages, while Asian customers prefer smaller multipacks. At the same time, your compliance database alerts you that new regulations on salt levels are about to go into effect in several of your target markets.

You want to respond before the regulations are implemented, for several reasons. You’ll need to update recipes, specifications, labels, and packaging. You’ll need to inform your suppliers, manufacturers, quality planners, financial controllers, logistics providers, and retailers. And you’ll need to get the replacement product into the affected markets, with auditable compliance with salt level requirements. Otherwise, you risk producing a large quantity of unsellable inventory.

This example shows us several things:

  • Insights must be as instant as possible.
  • Those insights might come from a variety of sources that your R&D folks didn’t previously have real-time access to.
  • Your products must be localized to a very granular level.
  • Even a minor change affects everything from recipes to packaging specifications, costs of materials, regulatory reporting, logistics providers, retailers, and on and on.

And that leads us to several conclusions:

  • Product data isn’t mission-critical only to R&D. It’s linked to every downstream business process.
  • A live, compliant, and collaborative environment, with the ability to instantly adapt to change, is a business requirement.
  • To achieve that requirement, product data must be part of business processes.
  • The platform the R&D team relies on must be linked to downstream platforms, and it must allow you to leverage and act on real-time insights.

Digital product innovation platform

Of course, the streaming of sensor data from connected things is still relevant in process industries. But for process manufacturers, the most important use cases are more around traceability, supply chain logistics, and product innovation. At some point, data from connected goods will allow new models that more tightly couple the supply chain with innovation cycles.

But a live and compliant product innovation platform achievable today. The question is whether you’ll get there before your competition does.

Come to SAPPHIRE NOW 2017 in Orlando, Florida from May 16 – 18th, 2017, and check out my session “Boost Visibility into Operations for Connected Products with SAP Leonardo” on Tuesday, May 16th, 2017 from 1-1:40 p.m. in Business Application BA324, or check out our R&D sessions.

Follow the conversation on @SCMatSAP and #SAPPHIRENOW.

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John McNiff

About John McNiff

John McNiff is the Vice President of Solution Management for the R&D/Engineering line-of-business business unit at SAP. John has held a number of sales and business development roles at SAP, focused on the manufacturing and engineering topics.

How 3D Printing Could Transform The Chemical Industry

Stefan Guertzgen

The history of 3D printing started 30 years ago with Chuck Hull, the Thomas Edison of the 3D printing industry, who introduced the first 3D printer. Since then, 3D printing (also known as additive manufacturing) has been used to create everything from food and other consumer goods to automotive and airplane parts.

Key drivers of adoption

The tremendous growth of 3D printing has been driven by three key factors. First, the cost is rapidly decreasing due to lower raw material costs, stronger competitive pressures, and technological advancements. Second, printing speeds are increasing. For example, last year, startup company Carbon3D printed a palm-sized geodesic sphere in a little more than 6 minutes, which is 25 to 100 times faster than traditional 3D printing solutions. Third, new 3D printers are able to accommodate a wider variety of materials. Driven by innovations within the chemical industry, a broad range of polymers, resins, plasticizers, and other materials are being used to create new 3D products.

While it’s difficult to predict the long-term impact 3D printing will have on the overall economy, it is safe to say that the it could affect almost every industry and the way companies do business. In fact, the chemical industry has already implemented 3D applications in the areas of research and development (R&D) and manufacturing.

Innovative feedstocks and processes

3D printing provides a vast opportunity for the chemical industry to develop innovative feedstock and drive new revenue streams. While more than 3,000 materials are used in conventional component manufacturing, only about 30 are available for 3D printing. To put this into perspective, the market for chemical powder materials is predicted to be more than $630 million annually by 2020.

Plastics and resins, as well as metal powders and ceramic materials, are already in use or under evaluation for printing prototypes, parts of industry assets, or semi-finished goods—particularly those that are complex to produce and that require small batch sizes. Developing the right formulas to create these new materials offers an opportunity for constant innovation within the chemical field, which will likely produce even more materials in the future. For example, Covestro, a developer of polymer technology, is developing a range of filaments, powders, and liquid resins for all common 3D printing methods; 3M, working with its subsidiary Dyneon, recently filed a patent for using fluorinated polymers in 3D printing; and Wacker is testing 3D printing with silicones.

The chemical industry is also in the driver’s seat when it comes to process development. About 20 different processes now exist that share one common characteristic: layered deposition of printer feed. The final product could be generated from melting thermoplastic resins (for example, laser sinter technology or fused deposition modeling) or via (photo) chemical reaction such as stereo-lithography or multi-jet modeling. For both process types, the physical and chemical properties of feed materials are critical success factors for processing and for the quality of the finished product.

New tools and techniques in R&D and operations

Typically, the laboratory equipment used to do chemical synthesis is expensive and complex to use, and it often represents an obstacle in the research progress. With 3D printing, it is now possible to create reliable, robust miniaturized fluidic reactors as “micro-platforms” for organic chemical syntheses and materials processes, printed in few hours with inexpensive materials. Such micro-reactors allow building up target molecules via multi-step synthesis as well as breaking down molecular structures and detecting the building blocks through reagents which could be embedded during the 3D printing process.

Micro-reactors can also be used as small prototypes to simulate manufacturing processes.

In addition to printing equipment used in laboratories, some chemical manufacturers are using 3D printers for maintenance on process plant assets. For example, when an asset fails because of a damaged engine valve, the replacement part can be printed on site and installed in real time. Creating spare parts in-house can significantly reduce inventory costs and wait time for deliveries, hence contributing to increase overall asset uptime.

For companies that do not want to print the parts themselves, an on-demand manufacturing network is available that will print and deliver parts as needed. UPS has introduced a fully distributed manufacturing platform that connects many of its stores with 3D printers. When needed, UPS and its partners print and deliver requested parts to customers.

Commercial benefits

Across all industries, 3D printing promises to reduce costs across the supply chain. For example, the ability to print spare parts on demand can save money through improved asset uptime and more efficient workforce management. 3D printing also helps control costs with reduced waste and a smaller carbon footprint. In contrast to traditional “subtractive” manufacturing techniques in which raw material is removed, 3D printing is an additive process that uses only the amount of material that is needed. This can save significant amounts of raw materials. In the aerospace industry, for example, Airbus estimates 3D printing could reduce its raw material costs by up to 90 percent.

From a manufacturing perspective, 3D printing can streamline processes, accelerate design cycles, and add agility to operations. Printing prototypes on site speeds the R&D development cycle and shortens time to market. Researchers can make, test, and finalize prototypes in days instead of weeks. Also, the ability to print parts or equipment on demand will eliminate expensive inventory holding costs and restocking order requirements and free up floor space for other purposes. In the U.S. alone, manufacturers and trade inventories for all industries were estimated at $1.8 trillion in August 2016, according to the U.S. Census Bureau. Reducing inventory by just 2 percent would be a $36 billion savings.

Barriers to adoption

As with most new technology, barriers must be overcome for this potential to fully be realized. One much-discussed but unresolved issue is intellectual property protection. Similar to the way digital music is shared, 3D printable digital blueprints could be shared illegally and/or unknowingly either within a company or by outside hackers.

In addition to digital files, users can print molds from scanned objects and use them to mass-produce exact replicas that are protected under copyright, trademark, and patent laws. This problem will continue to grow as companies move to an on-demand manufacturing network, requiring digital blueprints to be shared with independent fabricators. This poses a huge threat on companies losing billions of dollars every year in intellectual property globally.

Regulatory issues are slowing the adoption of 3D printer applications. This is especially applicable in the medical and pharmaceutical industries but has potential impact in many markets. For example, globally regulating what individuals will create with access to the Internet and a 3D chemical printer will be difficult. Also, as 3D printing drives small and customer-specific lot sizes, it will likely spur an explosion of proprietary bills of material and recipes, which will be hard to track and control under REACH or REACH-like regulations. Because this is a new frontier, many regulatory issues must be addressed.

In addition to legal and regulatory challenges, the industry has a long way to go in reliably reproducing high-quality products. Until 3D printing can match the speed and quality output requirements of conventional manufacturing processes, it will likely be reserved for prototypes or small-sized lots.

3D printing: a new frontier

While 3D printing has not reached the point of use for large-scale production or to consistently make custom products, ongoing innovations drive high demand. 3D printer market forecasts estimate that shipments of industrial 3D printers will grow by ~400% through 2021 to a value of about $26 billion. Global inventory value is estimated to be over $10 trillion. Reducing global inventory by just 5% would free up $500 billion in capital. Manufacturing overall is estimated to contribute ~16% to the global economy. If 3D printing just would capture 5% of this $12.8 trillion market, it would create a $640 billion+ opportunity.

3D printing will initially help chemical companies increase profitability by lowering costs and improving operational efficiency. However, the industry-changing opportunity is the chance to develop new feeds and formulations. The most successful chemical companies of the future will be the ones with the vision to begin developing and implementing 3D printing solutions today.

Learn more about SAPPHIRE NOW and secure your spot today!

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Stefan Guertzgen

About Stefan Guertzgen

Dr. Stefan Guertzgen is the Global Director of Industry Solution Marketing for Chemicals at SAP. He is responsible for driving Industry Thought Leadership, Positioning & Messaging and strategic Portfolio Decisions for Chemicals.

Live Product Innovation, Part 2: IoT, Big Data, and Smart Connected Products

John McNiff

In Part 1 of this series, we looked at how in-memory computing affects live product innovation. In Part 2, we explore the impact of the Internet of Things (IoT) and Big Data on smart connected products. In Part 3, we’ll approach the topic from the perspective of process industries.

Live engineering? Live product innovation? Live R&D?

To some people, these concepts sound implausible. When you talk about individualized product launches with lifecycles of days or weeks, people in industries like aerospace and defense (A&D) look askance.

But today, most industries—not just consumer-driven ones—need timely insights and the ability to respond quickly. Even A&D manufacturers want to understand the impact of changes before they continue with designs that could be difficult to make at the right quantity or prone to problems in the field.

The Internet of Everything?

Internet of Things (IoT) technologies promise to give manufacturers these insights. But there’s still a lot of confusion around IoT. Some people think it is about connected appliances; others think it’s just a rebranded “shop floor to top floor.”

The better way to think about IoT is from the perspective of data: We want to get data from the connected “thing.” If you’re the manufacturer, that thing is a product. If you buy the product and sell it to an end customer, that thing is an asset. If you’re the end customer, that thing is a fleet. Each stakeholder wants different data in different volumes for different reasons.

It’s also important to remember that the Internet has existed for far longer than IoT.

There’s a huge amount of non-IoT data that can offer useful insights. Point-of-sale data, news feeds, and market insights from social channels are all valuable. And think about how much infrastructure is now connected in “smart” cities. So in addition to products, assets, and fleets, there are also people, markets, and infrastructure. Big Data is everywhere, and it should influence what you release and when.

New data, new processes

It has been said that data in the 21st century is like oil in the 18th century: an immense, valuable, yet untapped asset. But if data is the new oil, then do we need a new refinery? The answer is yes.

On top of business data, we now have a plethora of information sources outside our company walls. Ownership of, and access to, this data is becoming complex. Manufacturers collecting data about equipment at customer sites, for example, may want to sell that data to customers as an add-on service. But those customers are likely using equipment from multiple manufacturers, and they likely have their own unique uses for the information.

So the new information refinery needs to capture information from everywhere and turn it into something that has meaning for the end user. It needs to leverage data science and machine learning to remove the noise and add insight and intelligence. It also needs to be an open platform to gather information from all six sources (products, assets, fleets, people, markets, infrastructure).

And wouldn’t it be great if the data refinery ran on the same platform as your business processes, so that you could sense, respond, and act to achieve your business goals?

Digital product innovation platform

If you start with the concept of a smart connected product, the data refinery — the digital product innovation platform — has five requirements:

  1. Systems design — Manufacturers need to design across disciplines in a systems approach. Mechanical, mechatronic, electrical, electronics, and software all need to be supported, with modeling capabilities that cover physical, functional, and logical structures.
  1. Requirements-linked platform design — Designers need to think about where and how to embed sensors and intelligence to match functional requirements. This will need to be forward-thinking to cover unforeseen methods of machine-to-machine interactions. In a world of performance-based contracts, it will be important to minimize the impact of design changes as innovation opportunities grow.
  1. Instant impact and insight environment — The platform must support fully traceable requirements throughout the lifecycle, from design concept to asset performance.
  1. Product-based enterprise processes — The platform needs to share model-based product data visually — through electrical CAD, electronic CAD, 3D, and software functions — to the people who need it. This isn’t new, but what’s different is that the platform can’t wait for complex integrations between systems. Think about software-enabled innovation or virtual inventory made possible by on-demand 3D printing. Production is almost real time, so design will have to be as well.
  1. Product and thing network — A complex, cross-domain design process involves a growing number of partners. That calls for a product network to allow for secure collaboration across functions and outside the company walls. Instead of every partner having its own portal for product data, the product network would store digital twins and allow instant sharing of asset intelligence.

If the network is connected to the digital product innovation platform, you can control the lifecycle both internally and externally — and take the product right into the service and maintenance domain. You can then provide field information directly from the assets back to design to inform what to update, and when. Add over-the-air software compatibility checks and updates, and discrete manufacturers can achieve a true live engineering environment.

Sound like a dream? It’s coming sooner than you think.

Come to SAPPHIRE NOW 2017 in Orlando, Florida from May 16 – 18th, 2017, and check out my session “Boost Visibility into Operations for Connected Products with SAP Leonardo” on Tuesday, May 16th, 2017 from 1-1:40 p.m. in Business Application BA324, or check out our R&D sessions.

Follow the conversation on @SCMatSAP and #SAPPHIRENOW.

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John McNiff

About John McNiff

John McNiff is the Vice President of Solution Management for the R&D/Engineering line-of-business business unit at SAP. John has held a number of sales and business development roles at SAP, focused on the manufacturing and engineering topics.

The Future of Cybersecurity: Trust as Competitive Advantage

Justin Somaini and Dan Wellers

 

The cost of data breaches will reach US$2.1 trillion globally by 2019—nearly four times the cost in 2015.

Cyberattacks could cost up to $90 trillion in net global economic benefits by 2030 if cybersecurity doesn’t keep pace with growing threat levels.

Cyber insurance premiums could increase tenfold to $20 billion annually by 2025.

Cyberattacks are one of the top 10 global risks of highest concern for the next decade.


Companies are collaborating with a wider network of partners, embracing distributed systems, and meeting new demands for 24/7 operations.

But the bad guys are sharing intelligence, harnessing emerging technologies, and working round the clock as well—and companies are giving them plenty of weaknesses to exploit.

  • 33% of companies today are prepared to prevent a worst-case attack.
  • 25% treat cyber risk as a significant corporate risk.
  • 80% fail to assess their customers and suppliers for cyber risk.

The ROI of Zero Trust

Perimeter security will not be enough. As interconnectivity increases so will the adoption of zero-trust networks, which place controls around data assets and increases visibility into how they are used across the digital ecosystem.


A Layered Approach

Companies that embrace trust as a competitive advantage will build robust security on three core tenets:

  • Prevention: Evolving defensive strategies from security policies and educational approaches to access controls
  • Detection: Deploying effective systems for the timely detection and notification of intrusions
  • Reaction: Implementing incident response plans similar to those for other disaster recovery scenarios

They’ll build security into their digital ecosystems at three levels:

  1. Secure products. Security in all applications to protect data and transactions
  2. Secure operations. Hardened systems, patch management, security monitoring, end-to-end incident handling, and a comprehensive cloud-operations security framework
  3. Secure companies. A security-aware workforce, end-to-end physical security, and a thorough business continuity framework

Against Digital Armageddon

Experts warn that the worst-case scenario is a state of perpetual cybercrime and cyber warfare, vulnerable critical infrastructure, and trillions of dollars in losses. A collaborative approach will be critical to combatting this persistent global threat with implications not just for corporate and personal data but also strategy, supply chains, products, and physical operations.


Download the executive brief The Future of Cybersecurity: Trust as Competitive Advantage.


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Unleash The Digital Transformation

Kadamb Goswami

The world has changed. We’ve seen massive disruption on multiple fronts – business model disruption, cybercrime, new devices, and an app-centric world. Powerful networks are crucial to success in a mobile-first, cloud-first world that’s putting an ever-increasing increasing amount of data at our fingertips. With the Internet of Things (IoT) we can connect instrumented devices worldwide and use new data to transform business models and products.

Disruption

Disruption comes in many forms. It’s not big or scary, it’s just another way of describing change and evolution. In the ’80s it manifested as call centers. Then, as the digital landscape began to take shape, it was the Internet, cloud computing … now it’s artificial intelligence (AI).

Digital transformation

Digital transformation means different things to different companies, but in the end I believe it will be a simple salvation that will carry us forward. If you Bing (note I worked for Microsoft for 15 years before experiencing digital transformation from the lens of the outside world), digital transformation, it says it’s “the profound and accelerating transformation of business activities, processes, competencies, and models to fully leverage the changes and opportunities of digital technologies and their impact across society in a strategic and prioritized way.” (I’ll simplify that; keep reading.)

A lot of today’s digital transformation ideas are ripped straight from the scripts of sci-fi entertainment, whether you’re talking about the robotic assistants of 2001: A Space Odyssey or artificial intelligence in the Star Trek series. We’re forecasting our future with our imagination. So, let’s move on to why digital transformation is needed in our current world.

Business challenges

The basic challenges facing businesses today are the same as they’ve always been: engaging customers, empowering employees, optimizing operations, and reinventing the value offered to customers. However, what has changed is the unique convergence of three things:

  1. Increasing volumes of data, particularly driven by the digitization of “things” and heightened individual mobility and collaboration
  1. Advancements in data analytics and intelligence to draw actionable insight from the data
  1. Ubiquity of cloud computing, which puts this disruptive power in the hands of organizations of all sizes, increasing the pace of innovation and competition

Digital transformation in plain English

Hernan Marino, senior vice president, marketing, & global chief operating officer at SAP, explains digital transformation by giving specific industry examples to make it simpler.

Automobile manufacturing used to be the work of assembly lines, people working side-by-side literally piecing together, painting, and churning out vehicles. It transitioned to automation, reducing costs and marginalizing human error. That was a business transformation. Now, we are seeing companies like Tesla and BMW incorporate technology into their vehicles that essentially make them computers on wheels. Cameras. Sensors. GPS. Self-driving vehicles. Syncing your smartphone with your car.

The point here is that companies need to make the upfront investments in infrastructure to take advantage of digital transformation, and that upfront investment will pay dividends in the long run as technological innovations abound. It is our job to collaboratively work with our customers to understand what infrastructure changes need to be made to achieve and take advantage of digital transformation.

Harman gives electric companies as another example. Remember a few years ago, when you used to go outside your house and see the little power meter spinning as it recorded the kilowatts you use? Every month, the meter reader would show up in your yard, record your usage, and report back to the electric company.

Most electric companies then made a business transformation and installed smart meters – eliminating the cost of the meter reader and integrating most homes into a smart grid that gave customers access to their real-time information. Now, as renewable energy evolves and integrates more fully into our lives, these same electric companies that switched over to smart meters are going to make additional investments to be able to analyze the data and make more informed decisions that will benefit both the company and its customers.

That is digital transformation. Obviously, banks, healthcare, entertainment, trucking, and e-commerce all have different needs than auto manufacturers and electric companies. It is up to us – marketers and account managers promoting digital transformation – to identify those needs and help our clients make the digital transformation as seamlessly as possible.

Digital transformation is more than just a fancy buzzword, it is our present and our future. It is re-envisioning existing business models and embracing a different way of bringing together people, data, and processes to create more for their customers through systems of intelligence.

Learn more about what it means to be a digital business.

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Goswami Kadamb

About Goswami Kadamb

Kadamb is a Senior Program Manager at SAP where he is responsible for developing and executing strategic sales program with Concur SaaS portfolio. Prior to that he led several initiatives with Microsoft's Cloud & Enterprise business to enable Solution Sales & IaaS offerings.