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How 3D Printing Will Energize The Chemical Industry - Part 1: Key Opportunity Areas

Stefan Guertzgen

It’s been nearly 30 years since Chuck Hull, the “Thomas Edison” of the 3D printing industry, introduced the first 3D printer. Since that time, 3D printing, otherwise known as additive manufacturing, has been used to create everything from shoes to airplane parts to even food. Although issues such as durability and speed have kept 3D printing from being used in mainstream manufacturing to date, the industry is making tremendous advancements.

The growing adoption of 3D printing by more markets is being driven by three primary developments. First, the cost of 3D printing is rapidly decreasing due to lower raw material costs, stronger competitive pressures, and technological advancements. According to a recent report by IBISWorld, the price of 3D printers is expected to fall 6.4% in 2016.

Second, printing is getting faster. Last year, startup company Carbon3D printed a palm-size geodesic sphere in a little over six minutes, which is 25 to 100 times faster than traditional 3D printing solutions. The company’s unique printing approach applies ultraviolet light and oxygen to resin in a technique called Continuous Liquid Interface Production to form solid objects out of liquid. Traditional additive printing is getting faster as well.

The third driver of 3D printing growth is the ability of new printers to accommodate a wider variety of materials. Aided by innovations within the chemical industry, a broad range of polymers, resins, plasticizers, and other materials are being used create new 3D products.

While it is impossible to predict the long-term impact 3D printing will have on the world, the technology likely will transform at least some aspects of how nearly every company, in nearly every industry, does business. In fact, the chemical industry already has implemented 3D applications in the fields of research and development (R&D) and manufacturing.

Developing innovative feedstock and processes

Chemicals is a highly R&D focused industry. In 2014, $59 billion was invested in R&D to discover new ways to convert raw materials such as oil, natural gas, and water into more than 70,000 different products. There’s a vast opportunity for 3D printing to develop innovative feedstock and corresponding revenue in the chemical industry . While over 3,000 materials are used in conventional component manufacturing, only about 30 are available for 3D printing. To put this in perspective, the market for chemical powder materials is predicted to be over $630 million annually by 2020.

Plastics, resins, as well as metal powders or 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 only required in small batch sizes. Developing the right formulas to create these new materials is an area of constant innovation within chemicals, which will likely produce even more materials in the future. Below are a few examples of recent breakthroughs in new materials for 3D printing.

  • Covestro, a leader in polymer technology, is developing a range of filaments, powders, and liquid resins for all common 3D printing methods. From flexible thermoplastic polyurethanes (TPU) to high strength polycarbonate (PC), the company’s products feature a variety of properties like toughness and heat resistance as well as transparency and flexibility that support a number of new applications. Covestro also offers TPU powders for selective laser sintering (SLS), in which a laser beam is used to sinter the material.
  • 3M, together with its subsidiary Dyneon, recently filed a patent for using fluorinated polymers in 3D printing. There are many types of fluorinated polymers, including polytetrafluoroethylene (PTFE), commonly known as Teflon, which often is used in seals and linings and tends to generated waste in production. The ability to print fluorinated polymers means they can be manufactured quickly and affordably.
  • Wacker is testing 3D printing with silicones. The process is similar to traditional 3D printing, but uses a glass printing bed, a special silicone material with a high rate of viscosity, and UV light. The printer lays a thin layer of tiny silicone drops on the glass printing bed. The silicone is vulcanized using the UV light, resulting in smooth parts that are biocompatible, heat resistant, and transparent.

The chemical industry is also in the driver’s seat when it comes to process development. Today about 20 different processes exist that have one common characteristic – layered deposition of printer feed. The final product could be generated from melting thermoplastic resins (e.g. Laser Sinter Technology or Fused Deposition Modeling) or via (photo) chemical reaction such as stereolithography or multi-jet modeling. For both process types, the physical and chemical properties of feed materials are critical success factors, not only for processing but also for the quality of the finished product.

3D printing of laboratory equipment

Laboratory equipment used for chemical synthesis is expensive and often difficult to operate. Machinery and tools must be able to withstand multiple rounds of usage during the product development process. With 3D printing, some of the necessary equipment can be printed at an affordable cost within the lab. Examples of equipment already being created with 3D printing include custom-built laboratory containers that test chemical reaction and multi-angle light-scattering instruments used to determine the molecular weight of polymers. Some researchers are also using 3D printers to create blocks with chambers used to mix ingredients into new compounds.

3D printing for manufacturing maintenance and 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 goes down due to a damaged engine valve, the replacement part can be printed onsite and installed in real time. Creating spare parts in-house can significantly reduce inventory costs and increase efficiency because there is no wait time for deliveries. Chemical manufactures are also started to print prototypes (e.g. micro-reactors) to simulate manufacturing processes.

For companies that don’t want to print the parts themselves, there is now an on-demand manufacturing network 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 the customer-requested part and deliver it. Connecting demand with production capacity is known as the “Uber of manufacturing.”

While not all parts will be suitable for 3D printing and work still needs to be done in terms of durability and materials, the potential reduction in inventory costs is significant. In the United States alone, manufacturers and trade inventories were estimated at $1.8 trillion in August 2016, according to the U.S. Census Bureau. Reducing inventory by just two percent would produce a $36 billion savings.

For more about 3D printing in the chemical industry, stay tuned for Part 2 of this blog, which will address commercial benefits, risks, and an outlook into the future. In the meantime, download the free eBook 6 Surprising Ways 3D Printing Will Disrupt Manufacturing.

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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.

Learn more about supply chain innovations at SAP.com or follow us on @SCMatSAP for the latest news.

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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.

Leveraging Contract Manufacturing Organizations In Life Sciences

Joseph Miles

The 21st century has been a remarkable and volatile time in the life sciences industry.

The onset of the patent cliff in the pharmaceutical and biotechnology sectors set forth a variety of strategies that have quite literally changed the face of the industry. Organizations, in an attempt to recoup the lost revenue and margin from patent expirations on blockbuster products, began acquiring companies at a pace that has never been seen before. What has emerged is a new and more focused industry. Non-strategic divisions where sold off in divestitures and focus areas were expanded with acquisitions that grew their pipeline, markets, and revenues.

In spite of all the M&A activity, the industry continues to explore new ways of improving their operating margins.   Outsourcing of operational processes has continued to increase in importance across the industry as organizations look for ways of reducing operational overhead.

Long used in the medical device and equipment sector, pharmaceutical and biotechnology companies have traditionally had more of an insource approach to manufacturing but that continued to change. Drug companies are not only leveraging contract manufacturing organizations (CMO) for less complex small molecule and active pharmaceutical ingredient production (API) but are now leveraging CMOs for more complex, large molecule products in spite of that manufacturing complexity.

This strategy is not without risk as organizations understand that you can outsource the process but you cannot outsource the accountability for that process. This dramatic transformation of business models, processes, and work strategies are focused on returning to the levels of profitability that had been accomplished earlier in their history.

If that isn’t complicated enough, the industry continues to see the emergence of global regulations that make manufacturing a complicated process to outsource. Global serialization, outlined in my previous blog, “The Rapidly Changing World of Serialization in Life Sciences,” now requires drug manufacturers to include a unique serial number on every vial of product produced. That serial number coordination with the CMO is challenging and is further complicated as the drug manufacturer is required to submit the information to global regulatory agencies who want to track the serial numbers to ensure the integrity of the product and, ultimately, the safety of the patient.

My team is very passionate about our ability to help global pharmaceutical, biotechnology, and medical device companies during these very challenging times. Life sciences companies should consider leveraging a cloud-based approach to direct materials that supports all aspects of direct material procurement. This should include processes to support supplier audits, approved vendor lists, purchase order releases, and blanket purchase orders. The cloud helps organizations reduce their capital expenses while also simplifying the IT support to enable the process.

Life sciences companies should also consider aggressively leveraging CMOs for the manufacturing of their products, even in this highly regulated industry. This would include the medical device and equipment segments that have leveraged CMO strategies for many decades but also drug companies inclusive of the serialized information.

Organizations are not only able to provide the CMO with all of the work orders, manufacturing instructions, routings, and standard operating procedures for regulated manufacturing, but they also have the ability to manage and generate all serial number information that would be applied to every vial of pharmaceutical and/or biotechnology product during the manufacturing process. This information can be delivered through a network that further simplifies the process and improves operational efficiencies, ultimately reducing the total cost of ownership to support the process.

Life sciences companies should not just be content with leveraging the cloud to enable the direct material and contract manufacturing processes for small and large molecule compounds, including serial number support, to meet global regulations. The network can be exploited further in the area of operational quality and production tracking. Manufacturing data, batch reports, quality information, and operational KPIs can be shared across the network to ensure the manufacturers have full visibility and transparency around the outsourced processes. This is highly strategic and reflects the underlying complexity of enabling outsourced manufacturing across all segments of the life sciences industry.

For more on digitalization in the life sciences industry, see Special Compliance Aspects And Quick Wins In The Life Sciences Industry.

 

 

 

 

 

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Joseph Miles

About Joseph Miles

Joseph Miles is Global Vice President pf Life Sciences at SAP. He is passionate about helping organizations improve outcomes for their patients and enable innovation across the health sciences value chain.

How Emotionally Aware Computing Can Bring Happiness to Your Organization

Christopher Koch


Do you feel me?

Just as once-novel voice recognition technology is now a ubiquitous part of human–machine relationships, so too could mood recognition technology (aka “affective computing”) soon pervade digital interactions.

Through the application of machine learning, Big Data inputs, image recognition, sensors, and in some cases robotics, artificially intelligent systems hunt for affective clues: widened eyes, quickened speech, and crossed arms, as well as heart rate or skin changes.




Emotions are big business

The global affective computing market is estimated to grow from just over US$9.3 billion a year in 2015 to more than $42.5 billion by 2020.

Source: “Affective Computing Market 2015 – Technology, Software, Hardware, Vertical, & Regional Forecasts to 2020 for the $42 Billion Industry” (Research and Markets, 2015)

Customer experience is the sweet spot

Forrester found that emotion was the number-one factor in determining customer loyalty in 17 out of the 18 industries it surveyed – far more important than the ease or effectiveness of customers’ interactions with a company.


Source: “You Can’t Afford to Overlook Your Customers’ Emotional Experience” (Forrester, 2015)


Humana gets an emotional clue

Source: “Artificial Intelligence Helps Humana Avoid Call Center Meltdowns” (The Wall Street Journal, October 27, 2016)

Insurer Humana uses artificial intelligence software that can detect conversational cues to guide call-center workers through difficult customer calls. The system recognizes that a steady rise in the pitch of a customer’s voice or instances of agent and customer talking over one another are causes for concern.

The system has led to hard results: Humana says it has seen an 28% improvement in customer satisfaction, a 63% improvement in agent engagement, and a 6% improvement in first-contact resolution.


Spread happiness across the organization

Source: “Happiness and Productivity” (University of Warwick, February 10, 2014)

Employers could monitor employee moods to make organizational adjustments that increase productivity, effectiveness, and satisfaction. Happy employees are around 12% more productive.




Walking on emotional eggshells

Whether customers and employees will be comfortable having their emotions logged and broadcast by companies is an open question. Customers may find some uses of affective computing creepy or, worse, predatory. Be sure to get their permission.


Other limiting factors

The availability of the data required to infer a person’s emotional state is still limited. Further, it can be difficult to capture all the physical cues that may be relevant to an interaction, such as facial expression, tone of voice, or posture.



Get a head start


Discover the data

Companies should determine what inferences about mental states they want the system to make and how accurately those inferences can be made using the inputs available.


Work with IT

Involve IT and engineering groups to figure out the challenges of integrating with existing systems for collecting, assimilating, and analyzing large volumes of emotional data.


Consider the complexity

Some emotions may be more difficult to discern or respond to. Context is also key. An emotionally aware machine would need to respond differently to frustration in a user in an educational setting than to frustration in a user in a vehicle.

 


 

download arrowTo learn more about how affective computing can help your organization, read the feature story Empathy: The Killer App for Artificial Intelligence.


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About Christopher Koch

Christopher Koch is the Editorial Director of the SAP Center for Business Insight. He is an experienced publishing professional, researcher, editor, and writer in business, technology, and B2B marketing. Share your thoughts with Chris on Twitter @Ckochster.

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In An Agile Environment, Revenue Models Are Flexible Too

Todd Wasserman

In 2012, Dollar Shave Club burst on the scene with a cheeky viral video that won praise for its creativity and marketing acumen. Less heralded at the time was the startup’s pricing model, which swapped traditional retail for subscriptions.

For as low as $1 a month (for five two-bladed cartridges), consumers got a package in the mail that saved them a trip to the pharmacy or grocery store. Dollar Shave Club received the ultimate vindication for the idea in 2016 when Unilever purchased the company for $1 billion.

As that example shows, new technology creates the possibility for new pricing models that can disrupt existing industries. The same phenomenon has occurred in software, in which the cloud and Web-based interfaces have ushered in Software as a Service (SaaS), which charges users on a monthly basis, like a utility, instead of the typical purchase-and-later-upgrade model.

Pricing, in other words, is a variable that can be used to disrupt industries. Other options include usage-based pricing and freemium.

Products as services, services as products

There are basically two ways that businesses can use pricing to disrupt the status quo: Turn products into services and turn services into products. Dollar Shave Club and SaaS are two examples of turning products into services.

Others include Amazon’s Dash, a bare-bones Internet of Things device that lets consumers reorder items ranging from Campbell’s Soup to Play-Doh. Another example is Rent the Runway, which rents high-end fashion items for a weekend rather than selling the items. Trunk Club offers a twist on this by sending items picked out by a stylist to users every month. Users pay for what they want and send back the rest.

The other option is productizing a service. Restaurant franchising is based on this model. While the restaurant offers food service to consumers, for entrepreneurs the franchise offers guidance and brand equity that can be condensed into a product format. For instance, a global HR firm called Littler has productized its offerings with Littler CaseSmart-Charges, which is designed for in-house attorneys and features software, project management tools, and access to flextime attorneys.

As that example shows, technology offers opportunities to try new revenue models. Another example is APIs, which have become a large source of revenue for companies. The monetization of APIs is often viewed as a side business that encompasses a wholly different pricing model that’s often engineered to create huge user bases with volume discounts.

Not a new idea

Though technology has opened up new vistas for businesses seeking alternate pricing models, Rajkumar Venkatesan, a marketing professor at University of Virginia’s Darden School of Business, points out that this isn’t necessarily a new idea. For instance, King Gillette made his fortune in the early part of the 20th Century by realizing that a cheap shaving device would pave the way for a recurring revenue stream via replacement razor blades.

“The new variation was the Keurig,” said Venkatesan, referring to the coffee machine that relies on replaceable cartridges. “It has started becoming more prevalent in the last 10 years, but the fundamental model has been there.” For businesses, this can be an attractive model not only for the recurring revenue but also for the ability to cross-sell new goods to existing customers, Venkatesan said.

Another benefit to a subscription model is that it can also supply first-party data that companies can use to better understand and market to their customers. Some believe that Dollar Shave Club’s close relationship with its young male user base was one reason for Unilever’s purchase, for instance. In such a cut-throat market, such relationships can fetch a high price.

To learn more about how you can monetize disruption, watch this video overview of the new SAP Hybris Revenue Cloud.

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