Ask an Expert: Michael Fornasiero

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For this edition of our “Ask an Expert” series, we interviewed Michael Fornasiero, Manufacturing USA specialist for Empire State Development’s Division of Science, Technology & Innovation, about current issues and future possibilities in the field of digital manufacturing. In this role, he works to drive advanced manufacturing technology adoption and new market opportunities for manufacturers across New York State.
What are the goals behind “going digital” in design and manufacturing operations?

Digital Manufacturing and Design (DM&D) is an integrated approach that brings together software, data, sensors and control systems to model, simulate, analyze, control and optimize both the performance of a product and the manufacturing and business systems that produce it. The connectivity of data and systems between all elements of the product lifecycle creates channels for
real-time collaboration between product stakeholders and enables us to make smarter, more efficient and more fully informed business decisions.
DM&D technologies enable the creation of a “digital thread” by breaking down traditional silos of data and establishing a communication framework across the enterprise and supply chain. This digital thread makes it possible to support dynamic assessment of a product or system’s current and future capabilities, and it supports informed decision making throughout its life cycle. The collection of data along with a physics-based understanding of the product or system can support a “digital twin” of the product or asset, where collected design specifications, engineering models, manufacturing information and operational data support optimized performance, predictive maintenance, trace-ability and design feedback.
How should small and medium manufacturers approach new technology adoption across their operations?

As a business reflects on the adoption of new technologies in their operations it is critical for them to recognize that there is no one-size-fits-all or single solution for their digital journey. As an organization plans to drive digital technologies across their operations, there are four stages to consider:

  1. Standardize – Establish efficient workflows and processes throughout your business operations. A stable foundation of efficient business processes and an understanding of data in your enterprise is critical to successful adoption of digital technologies. A lack of focus at this stage will lead to further headaches later as more systems across the enterprise are integrated. This is a great time to apply “lean” principles to your operations.
  2. Automate and Digitize – Apply new hardware or software systems that either enhance or automate business capabilities. At this stage the organization should focus on identification of operational pain points and large silos of data. This stage is an opportunity to pilot automation efforts on the manufacturing floor, as well as to adopt software solutions that support greater data transparency throughout the organization. Critical to adopting new technologies at this stage is an awareness of how future systems will network and integrate and avoiding a complex mix of different automation products and software systems.
  3. Network and Integrate – Build connectivity between systems across the enterprise and establish connections between different hardware and software systems. Connections between systems in IT and OT networks are solidified and the networks are merged. Break down any remaining silos of data, insight and expertise within the organization. Are staff members getting the information they need? Is data in the organization no longer feedforward only, but instead providing the opportunity for feedback throughout the product lifecycle and across operational areas?
  4. Intelligent Systems – Leverage data throughout the enterprise to create systems that guide and automate actions. With an established understanding of the organization’s operations, products, supply chain and consumers, as well as the networking of systems, it becomes possible to automate tasks based on available data. This can include the automatic ordering of materials from suppliers, the notification of assets that need maintenance and the optimized execution of manufacturing operations.

What new opportunities do these technologies enable and what are some examples of success?

  • Design – New suites of design (CAD) software often integrate elements of simulation software and machine tool programming (CAM) into a single platform. These tools can make it easier to leverage product models from the office to the shop floor and open new avenues of collaboration across the product lifecycle. Input from manufacturing staff can be conveyed back to designers more readily to improve product design, designers can gain a better sense of the impact of their design decisions on product performance and manufacturing complexity, and more.
  • Manufacturing – Tools that connect once siloed machine data with OT networks can provide greater insight into machine utilization, performance, maintenance needs and even improve shop floor scheduling.
  • Operations – Software systems and hardware distributed across the manufacturing environment can help provide insight into how a factory is performing at the asset, product, staff and inventory levels, supporting the execution of daily operations.
  • Supply Chain – Greater connectivity of data in the factory and across supply chain partners can make sure inventory levels at production stations never run out, and that production materials are ordered from suppliers when target inventory levels are reached. Supplier quality management systems can make it easier to align quality data of supplied materials to the products produced.
  • Worker Support – New software and hardware tools support improved worker performance and quality. Augmented reality systems and digital work instructions can be much easier to interpret than standard written work instructions and often have the added benefit of being able to collect worker performance and manufacturing quality data directly. These tools can make training new employees and driving manufacturing process improvement easier. Connected tools such as torque wrenches and gauges can make it easier to collect quality data while reducing risks around improper assembly or measurement. Collaborative robotics can even be leveraged to support the flexible automation of repetitive tasks on the shop floor and do not require the typically complex safety cells and programming regimens of traditional robotics systems.
  • Connectivity – New devices and platforms make it easier to experiment with new technology impacts on your manufacturing floor without having to make considerable infrastructure and software investments. These solutions can range from devices that allow legacy (non-digital) machines to send out data to nearly plug-and-play wireless predictive maintenance sensors that can monitor motor or asset performance for signs of degradation or imminent failure.

What are some common pitfalls?

  • Building digital systems on top of inefficient business and manufacturing processes – It is best to optimize the processes within an organization in an “analog” way before new digital technologies are applied. It becomes far more difficult to improve processes after technologies have been layered on top.
  • Collecting all the data – Setting up historians and building data lakes will only be useful if you understand what the data can tell you and how you will identify useful insights from it. Otherwise you run the risk of drowning in the data and only finding value after missing an important event. Collect focused, insightful and actionable data as a priority; all data streams must have a purpose.
  • Not planning ahead – As more systems within an organization are digitized and integrated between one another, that “affordable” ERP system, or other software suite, that was partially deployed years ago or collection of different PLCs and automation controllers may prove to be new stumbling blocks in integration after having solved old “in the moment” problems.
  • Failing to update your company’s intelligence assets – A company leveraging advanced technologies will never benefit from their true potential unless their staff understand how to interact with the technologies. Help employees understand the big picture of what the company is doing to adopt new technologies and make sure they are supported to successfully leverage new tools.
  • Business as usual in the digital age – New technologies and expanded levels of data connectivity across the organization provide new opportunities to improve products, processes and how we interact. Businesses that simply pass their work over the cubicle wall or between departments to the next person in line will fail to prosper from new avenues of collaboration and opportunities for feedback. Modern design and simulation software coupled with new manufacturing and testing technologies enable product innovation to occur at a faster pace and to incorporate opportunities for near continuous refinement of designs and production processes.

How can small manufacturers learn more and get support?

Connect with business and technology experts across New York State’s extensive manufacturing assistance network. Assets across the state supported by Empire State Development’s (ESD) Division of Science, Technology and Innovation (NYSTAR) include the Manufacturing Extension Partnership centers, of which FuzeHub is a part; Centers for Advanced Technology (CATs); and Centers of Excellence (COEs).
Join a growing community of digital manufacturing and design technology leaders and learn more about emerging industry trends and research at the Digital Manufacturing and Design Innovation Institute (DMDII). DMDII is part of the Manufacturing USA network facilitating technology transition by connecting people, ideas, and technologies across industry, government and academia.  In partnership with UI LABS and the Department of Defense, DMDII equips U.S. factories with the digital tools and expertise they need to begin building every part better than the last.
Learn more about Digital Manufacturing and Design technologies by taking part in the massive open online course (MOOC) series, Digital Manufacturing and Design Technology. Over a series of nine courses, learners are introduced to a broad range of digital manufacturing and design technologies and shown how they can be used throughout a product’s lifecycle. The full series includes 40 hours of instruction, assessments, peer interactions and a final project. The series was developed by the University at Buffalo (UB), led by The Center for Industrial Effectiveness (TCIE), the business outreach center of UB’s School of Engineering and Applied Sciences, in coordination with the SMART (Sustainable Manufacturing and Advanced Robotic Technologies) Community of Excellence, the Center for Educational Innovation and industry partners including Siemens PLM, SME, the Association for Manufacturing Technology, Moog Inc. and Buffalo Manufacturing Works. Individual course content, including videos and readings, can be accessed at no cost through “audit” links on each individual course page; the fee to enroll in the series, with access to all assignments and the opportunity to earn a specialization completion certificate, is $49 per month. To enroll, visit, create an account and register for the Digital Manufacturing and Design Technology Specialization.
Michael Fornasiero can be reached at [email protected].


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