Category

Internet of Things (IoT)

2016: Trends, Predictions and Opportunities

By Augmented / Virtual Reality, Automotive, Internet of Things (IoT), Service Lifecycle Management (SLM) 5 Comments

The Industrial Internet of Things (IIoT): Still More Talk Than Walk

The torrent of breathless headlines, rosy economic predictions and novel business ideas will continue in 2016, but, overall, there will be more talk than walk. At the same time, the promise, even if overly optimistic, is real, meaningful and worth pursuing, and the number of companies exploring it will continue to grow.

Excitement over IIoT, bolstered by increased corporate budgets, will continue to fuel new initiatives and projects, although they will be mostly driven by the lines of business, resulting in one-off non-scalable implementations. Lack of adequate standards, and sometimes the availability of multiple of standards will contribute to the proliferation of “limited edition” IIoT.

Security and privacy concerns will linger.  Demonstrations of hackable devices and vulnerable industrial networks, especially with the United States presidential election campaigns that keep cybersecurity and rogue forces in the public eye, will impede large scale implementations, especially of public IIoT systems.  Companies that offer robust methods for securing the IIoT will get the attention of investors and industrial companies alike. Read More

Knowledge Based Product Development

By Design Reuse, Innovation, Internet of Things (IoT), Manufacturing, PLM No Comments

Lack of ongoing insight into product operation and the interaction with users is a major contributor to the persistence of a knowledge gap that plagues many product organizations, reduces efficiency and stifles innovation.

What drives this knowledge gap? A number of general trends impact companies in most industry sectors and product types.

  • Technology complexity and, in particular, the increased reliance on complex embedded control software.
  • Elongated and fragmented supply chains that support global operations.
  • Meeting global markets demand results in lower volume of configuration-specific product instances.
  • Accelerated egress of an aging workforce from the workplace.

The impact of the growing knowledge gap is most recognized and frequently discussed in the context of equipment maintenance and repair, which is a knowledge intensive activity. Another area were closing the knowledge gap has significant benefits is engineering change management.

Organizations often speak about the need to collect and formalize “tribal knowledge” to close the gap between the knowledge needed to perform a complex takes or reach a decision, and the knowledge and experience the person performing this task has access to.

In a previous article I discussed the severe myopia that exists in many product companies: most engineering organizations lose sight of their products once they are sold or installed in the field. In some manufacturing companies this happens even earlier, during the transition to manufacturing engineering and before the product enters volume production. Once a product is in use, there is only a trickle of information in the form of service records and warranty claims. But many organizations dismiss critical maintenance and warranty information as merely operational and cost of doing business and aren’t leveraging its full potential.

Knowledge Based Product Development

Product organizations cannot have a true and complete view of a product and how customers are using it unless they can continue to observe it while it is in use. They must monitor and analyze products throughout their lifecycle, gauge their performance, quality and uptime, how users are interacting with the products, and how well they meet market expectations overall.

This rich multidisciplinary insight extends beyond design information. It includes multifaceted data from a variety of sources and disciplines and includes manufacturing, supply chain, filed operations and service and maintenance. The data can be aggregated from multiple sources, including real-time data such as IoT, maintenance record and customer experience.

The aggregation, classification and analysis of this data provides critical insight to embellish and enhance an organizational knowledge library for subsequent iterations of product design, manufacturing process engineering, and service planning.  reinforced by analytics, case-based reasoning (CBR), and similar tools to collect, analyze and vet information.

Product organizations cannot afford operating with blinds that prevent visibility to downstream processes. They should not ignore the value of information collected throughout the product lifecycle. They must establish knowledge processes, governed by PLM software, to maximize the utility and benefit of product lifecycle information.

(Photo: FreeDigitalPhotos.net)

Elephant Monument for Champs-Élysées (Jean-Jacques Lequeu, 1758)

Design for IoT or Design by IoT?

By Internet of Things (IoT), Manufacturing, PLM No Comments

The Internet, mobile devices and cloud computing are drastically changing manufacturing. Software control systems embedded in smart devices and connected machines form a network of sensors and actuators that exchange information autonomously and can monitored and controlled online.

The potential impact of the Industrial Internet of Things (IIoT) and Industry 4.0 are undisputed. While industry pundits and technology vendors may dispute the exact size and growth rate of the IIoT, there is a general consensus that the space offers significant business value and will be transformative indeed.

Are the smart connected devices—or the “things”—that form the IIoT the same machines and devices we know and understand today, only connected? Or do we need to invent new paradigms to define system functionality and product architecture in order to realize the value of the IoT? Read More

Is Your PLM System Running Out of Steam?

By Internet of Things (IoT), PLM No Comments

The manufacturing world continues to change at an accelerated speed. New complexities driven by embedded software and cyber-physical system interactions introduce new design and testing challenges. Fierce competition and demanding customers force product companies to incorporate new business models and rethink everything, from product architecture to supply chains.

Can your PLM system handle these pressures?

With roots in a CAD-centric world that revolved around bill of materials data management and simple workflow, traditional PLM software tools are already highly taxed.  They support different design disciplines in parallel: mechanical and electrical design, hardware and software, and manage multiple rapidly reiterating development cycles. And top these off, the number of product configurations and variants is exploding.

PLM systems are running out of steam!

Manufacturing organizations are changing their business thinking and design philosophy to harvest the value promised by the Internet of Things (IoT) and Industry 4.0, in which software control systems embedded in smart devices and connected machines form a network of sensors and actuators that are continually monitored and controlled online.

The potential impact of the Industrial Internet of Things (IIoT) and Industry 4.0 are undisputed. But are engineering and design tools—PLM software in particular—equipped to handle the complexities of designing IoT-enabled devices?

The simple answer is no.

Not unless product companies take the time and effort to rethink their product lifecycle management strategies. Manufacturers need to reevaluate how ready their product development and methodologies are to tackle the impending hurdles posed by product complexity. They need to determine their organizational maturity to incorporate new business models. And they must develop new approaches to position PLM as the underpinning for restructuring the product organization and harvest the value in the Internet of Things.

If you’d like to hear more, join industry experts in the Product Innovation Conference Boston on November 17th and 18th. I will discuss key product lifecycle IoT design elements:

  • Design for IoT
  • Design for the Business of IoT
  • Design for IoT or Design by IoT?

See you there.

Section perpendiculaire du moulin des Verdiers (Jean-Jacque Lequeu, 1778)

Industrial IoT and Equipment Service

By Field Service, Internet of Things (IoT) One Comment

Despite criticism of being overly hyped, IoT technology remains top of mind in many organizations and  will continue to dominate conversations and drive new investments, and for many good reasons. There are numerous areas where Industrial IoT (IIoT) offers clear and significant business value potential. One of the better articulated use cases is service lifecycle management (SLM) and, in particular, remote monitoring and diagnostics.

The annals of equipment service reveal that remote diagnostics and telematics in general are anything but a new concept. In the 80s and 90s, IBM, Digital Equipment, Xerox and other product companies build equipment capable of “phoning home” using commercial telephone lines to report a malfunction, and remote access to enable equipment troubleshooting.

Why IoT, Why Now?

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