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Data-Driven Predictive Analytics Can Transform Plant Engineering

Pat Waurzyniak
By Patrick Waurzyniak Contributing Editor, SME Media

Manufacturing Engineering: How important is machine monitoring/plant diagnostics and the Industrial Internet of Things [IIoT] for manufacturing productivity?

Chad Stoecker: It used to be enough to rely on alarms and trips to start the maintenance and troubleshooting process in a plant. This is a reactive process that results in production losses and expenditure of unnecessary maintenance dollars. Today, most industries want more efficient solutions.

Plant personnel can use data to determine when equipment problems start, instead of waiting until the asset is offline or has approached an alarm limit. Acting early will help companies have the time to make better economic decisions.

Also, there are some companies that have a tendency to do things the way they have always done them. They might not yet understand the value of data-driven maintenance programs. However, the industry is moving away from maintenance based solely on the recommendations of the OEM that sold the equipment or time-based maintenance intervals. Those companies that are able to move to data-driven programs will realize significant performance improvements and financial savings.

And, all areas of the plant are going to be data-driven. Maintenance and reliability engineers can determine what maintenance to take and what maintenance actions can be avoided. Process and operations personnel can use data to determine the most efficient way to run the plant and what activities are costing the company money. Business executives can use data to make better decisions related to the demands they get from the market. Data analytics can transform the plant from end to end.

ME: What types of predictive analytics is GE Digital’s Industrial Performance and Reliability Center [IPRC] currently using for improving machine reliability, uptime, etc.?

Stoecker: Our solutions leverage the latest in cutting edge data analytics techniques and we support our solutions with industry experts with decades of reliability engineering expertise. GE’s digital industrial software has decades of expertise built into the software from industry subject matter experts and data scientists. This expertise enables plant engineers to take advantage of GE’s collective experience with equipment to make better decisions, without having to be a data scientist. We believe that software and analytics empower people to make better decisions.

ME: What specific software applications are associated with IPRC’s analytics efforts, and how are they used?

Stoecker: Asset Performance Management [APM] software, like the Predix-based solution GE offers, have end-to-end capabilities that allow companies to switch more easily to a more data-driven program by focusing on their particular problem area. GE offers starter kits to allow companies to experience this new way of doing maintenance, and GE offers consulting services to help companies plot their course moving forward in the Industrial Internet.

Data analytics are used extensively throughout GE factories producing a wide range of products including the large turbines used for power-generation applications.

It is important to recognize that companies can get a lot of value from their existing sensors by using predictive analytics technologies. Companies can increase uptime and reliability with sensors they have already installed. In addition, predictive analytics solutions, like our new APM solutions powered by Predix, will make recommendations about which sensors should be prioritized for maintenance during an outage or which sensors should be prioritized for retrofit to existing equipment.

Industrial software solutions can analyze and prioritize data to allow companies of all kinds to make better use of the sensors that they already have installed. These solutions can then prescribe what instrumentation will drive the most value in that environment if they could be added to the system. Moving forward, every new piece of equipment will have more instrumentation and data streaming off of it than the equipment it replaced.

ME: How is this type of predictive analytics employing what’s been called the ‘machine whisperer’ in helping to improve plant performance?

Stoecker: There are a lot of people with decades of experience in machine maintenance, those that we sometimes refer to as ‘machine whisperers,’ who are leaving industry today and whose expertise is almost impossible to replace. These people knew what was wrong with a piece of equipment just by touch and feel. This talent is being replaced by data.

Our goal is to offer the next-generation workforce a combination of people, processes, and technology built into software solutions that help them to make good decisions.

Predictive analytics give plant engineers the right information at the right time. Early warning gives plant engineers the time to evaluate risk and create better maintenance schedules. This allows companies to also realize less downtime due to surprises and shorter outages that are better planned. Predictive analytics can allow for better management of spare parts and less waste due to unnecessary maintenance actions.


Siemens PLM Software (Plano, TX) and Local Motors (Phoenix) announced the expansion of an existing partnership April 25. Siemens’ PLM software now will be used by Local Motors to optimize the development and large-scale 3D printing of automobiles. The partnership combines the power of Siemens’ PLM software technology with Local Motors’ capabilities in co-created and 3D-printed vehicles with direct digital manufacturing (DDM) processes.

With a shared vision for the future of product development, Local Motors plans to enhance productivity in its Local Motors Labs program by leveraging Siemens’ expertise in creating “digital twins” while Siemens expects to further enhance its digital enterprise software suite to support the latest advances in additive manufacturing and 3D printing.

Siemens PLM and Local Motors have been partners since 2011, the companies said. “Today’s announcement takes that partnership to the next level by enabling our community of co-creators to innovate even faster,” said Jay Rogers, CEO of Local Motors. “We developed the world’s first co-created vehicle and 3D-printed car, and now our LM Labs program is providing the world’s makers with a way—both online and offline—to create new technologies to advance the future of transportation.”

Open to anyone, LM Labs has employed Siemens’ Solid Edge 3D modeling software, and using the program’s synchronous technology, it is able to seamlessly import into Solid Edge non-native CAD models from design collaborators around the world, and then use Solid Edge to easily edit these models. The expanded partnership includes more use of Solid Edge while adding Siemens’ NX CAD/CAM software and the company’s Fibersim portfolio of software to all Local Motors facilities worldwide.

Robotics manufacturer KUKA AG (Augsburg, Germany) and Infosys Ltd. (Bengaluru, India), a provider of business consulting, information technology and outsourcing services, announced April 27 at Hannover Messe that the companies would collaborate in a partnership to jointly develop solutions to support manufacturers embracing Industry 4.0.

The partnership’s goal is to develop a software platform that allows customers to collect, evaluate and use data for improving their own processes. KUKA will work to extend the connection of machines with the cloud by establishing an Industry 4.0 Cloud Platform. These software and services will be developed by a newly established subsidiary of KUKA, connyun. The name connyun is comprised from the English word ‘connect’ and ‘yun’, the Chinese term for cloud.

“We want to offer our customers access to a wide ecosystem of partners. We are inviting partners and startups to offer their services on our platform,” said Christian Schlögel, CTO of KUKA and CEO of connyun. “With our own solutions and the expanded range of partner solutions, we can offer customers a wide breadth of production and logistics processes optimization.”


Database software giant Oracle Corp. (Redwood Shores, CA) on April 28 announced it had entered into a definitive agreement to acquire Textura Corp. (Deerfield, IL), a supplier of construction contracts and payment management cloud services, for $26.00 a share in cash. The deal is valued at approximately $663 million, net of Textura’s cash.

Textura’s cloud services process $3.4 billion in payments for over 6000 projects each month. The companies will combine Oracle Primavera and Textura will form the Oracle Engineering and Construction Global Business Unit, offering a comprehensive cloud-based project control.

Oracle’s board unanimously approved the transaction, which is expected to close in 2016, subject to Textura stockholders tendering 66 2/3% of Textura’s outstanding shares and derivative securities exercised prior to the closing in the tender offer, and customary closing conditions.

OpenText Corp. (Waterloo, ON, Canada) on April 27 announced it has entered into a definitive agreement to acquire ANXeBusiness Corp. (ANX; Southfield, MI), a provider of cloud-based information exchange services to the US auto and healthcare industries.

The purchase price is approximately $100 million, according to OpenText, a supplier of enterprise information management (EIM) software. The deal is expected to generate approximately $30 million of annualized revenue and be immediately accretive. ANX is expected to be integrated into the OpenText Business Network, a portfolio of cloud solutions and software designed for efficient, secure supply-chain and business collaboration between organizations.

New Releases

Accenture plc (Dublin, Ireland) and Dassault Systèmes (Paris) announced April 25 at Hannover Messe that the companies are building a proof of concept to show how digital technologies can improve efficiency and create more agile manufacturing in industries such as heavy industrial equipment and aerospace.

Working with a large industrial equipment company, Accenture and Dassault Systèmes are building and implementing a three-phase solution that harnesses digital technologies to create a link between engineering and the manufacturing shop floor for non-repetitive manufacturing companies. The adaptive solution provides a new level of continuity for product assembly including the sequence in which parts are built and provides a better level of insight into the process for engineers and the assembly staff.

The first phase of the agile manufacturing solution creates the theoretical assembly sequence required to build a product such as a train, airplane or digger. Phase two helps create, optimize and replan quickly an operational plan and schedule for each worker on the shop floor. The third phase creates a digital display of the schedule for each worker so they are able to refer to it. These three phases use Dassault Systèmes’ solutions.

Accenture and Dassault Systèmes are creating a solution that provides a new digital link between the engineering team and the shop floor, allowing for real-time changes in the schedule. The agile manufacturing solution can also provide insight and risk assessment for any proposed changes to a product or the assembly schedule before they are made, greatly reducing downtime and creating more agile manufacturing.

This article was first published in the June 2016 edition of Manufacturing Engineering magazine.

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