BorgWarner Increases Overall Equipment Effectiveness With Lean Software Product

BorgWarner Increases Overall Equipment Effectiveness With Lean Software Product

Software solution underlies project to improve Overall Equipment Effectiveness (OEE) in a BorgWarner plant. Lean practitioners once hated automation and software. Over the years, though, appropriate use of these technologies actually improves Lean performance. Here is a case study.

The cloud-based lean manufacturing solution provider Leading2Lean was part of a Total Productive Maintenance (TPM) solution that helped auto powertrain maker BorgWarner increase Overall Equipment Effectiveness of an operating area by 10 percent in six months when coupled with its TPM implementation, at its Seneca, SC plant.

Soon after implementing Leading2Lean, the plant began to resolve inefficiencies and frustrations with a system that allowed them to better identify production weaknesses. The plant handled an increase in product demand while still improving First Pass Yield ratios, reducing scrap, maintaining high production levels, better utilizing labor resources, and improving overall communication with management and employees.

The team maintained high levels of operational availability—some areas as high as 90 percent. Area employees drive this process optimization—scheduling, planning and monitoring performance of machines on their lines—all through the Leading2Lean product.

“It’s as easy to use as Facebook or Google,” said Will Venet, TPM Implementation Leader at BorgWarner. Experienced managers also find the system intuitive. “What a reliability engineer took decades of experience to learn can be learned in an afternoon,” Venet said.

Plant Maintenance Engineer Rodney Osborne said the crew used to use “gut checks” to guess which machine needed maintenance or how much money they spent on spare parts for a machine. “But now with Leading2Lean we do a simple report and it tells us—there’s no ambiguity,” Osborne says. “It takes the gut check out of it. It’s real data, and it’s without question a much better way of doing business for us.”

Initially, some employees thought bringing in the Leading2Lean system was an oversight effort, like “Big Brother,” but results soon changed their minds. Today, there is a far more collaborative relationship between Production and Maintenance, and team members at all levels feel more engaged because they are empowered to identify and produce solutions for continuous improvement.

Downtime reductions were driven largely by the engagement of operators. This was because they had easy access to the data and the manipulation of that data to drive improvements in preventative maintenance. What used to take four or five days to analyze through laborious data mining can now be done in 20 minutes.

“The collaborative efforts the team is making for continuous improvement are influenced by having a tool that is universally appreciated,” Venet said. “I’ve come to appreciate that what Leading2Lean is really doing is helping us to be a better manufacturer all around.”

Without Analytics The IIoT Is Meaningless

Without Analytics The IIoT Is Meaningless

Connecting your plant devices through the Industrial Internet of Things (IIoT) generates lots of data; but, without powerful analytics and visualization, it’s all meaningless.

Therefore, Plex today announced a new analytics product.

The IntelliPlex Production Analytic Application, available now, taps IIoT data to provide manufacturing leaders with enterprise-wide insight into the performance of production operations, including processes and equipment on the shop floor.

This application adds to Plex’s IntelliPlex Analytic Application Suite, which includes applications for sales, order management, finance and procurement. This suite, with the addition of production analytics, delivers to manufacturers the industry’s most comprehensive cloud analytics, uniquely providing visibility all the way down to the shop floor.

The Plex Manufacturing Cloud is a comprehensive platform for manufacturing enterprises, connecting suppliers, customers, people, equipment, materials and finances across multiple facilities to form the technology backbone of an organization. Plex uses real-time IIoT connections as a core mechanism for managing manufacturing operations and enterprise resource planning.

That comprehensive view means Plex not only streamlines and automates operations, but also enables unprecedented access to companywide information including IIoT data. The IntelliPlex suite of analytic applications turns that data into configurable, role-based, decision support dashboards – with deep drill-down and drill-across capabilities. Plex first introduced the IntelliPlex Analytic Application Suite in 2016 with turnkey analytics for sales, order management, procurement and finance professionals.

  • The IntelliPlex Production Analytic Application provides insight into key performance measures such as overall equipment effectiveness (OEE), scrap rates, first pass yield, inventory turns, on-time jobs and machine availability.
  • IntelliPlex is configurable, so users can create custom performance dashboards and combine metrics to form their own analysis based on the wealth of data stored in the Plex Manufacturing Cloud.
  • IntelliPlex analytics are also drillable, enabling users to instantly go from top-line performance analysis directly into data and details across plants, time and geographies.
  • IntelliPlex applications are easy to activate as part of the Plex Manufacturing Cloud, and can be quickly extended and configured to match an organization’s evolving needs over time.
  • The Production Analytic Application is available now.

Plex is planning to deliver additional analytic applications, including supply chain and human capital management. All applications are accessible to customers without the need for a lengthy implementation process.

“At Plex, we know that the best manufacturing organizations are built on the shop floor and that operational excellence is the foundation of product quality, company growth, and profitability,” said Karl Ederle, group vice president of products for Plex. “The IntelliPlex Production Analytic Application is unique because it provides an enterprise-wide view of manufacturing performance, combined with the ability to tap into the IIoT signals from equipment on a specific production line. Plex now offers customers analysis of their organization that truly spans from shop floor equipment to the financial bottom line.”

“This is not an IT tool, it’s an empowerment tool,” said Janice D’Amico, Plex specialist lead, Hatch Stamping. “The IntelliPlex Production Analytic Application has given Hatch access to accurate, near real-time data cross-enterprise that is user-friendly – easy to create, understand and share. We see this application being used at all levels of the organization to make better business decisions. The opportunities are endless.”

“In many manufacturing organizations, there is a communication breakdown between the front office and the shop floor,” said Alexi Antonio, Plex Analytics product lead. “Because the three OEE production metrics—performance, quality, and availability—are not expressed in monetary units, daily efforts to improve processes using OEE alone do not always translate into bottom-line savings. Plex puts OEE and financial metrics into a single dashboard, for the first time giving manufacturing leaders the ability to see and manage complete business performance.”

Real-Time OEE Performance Management

Real-Time OEE Performance Management

One of my customers back in the 90s established an OEE office and placed an OEE engineer in each plant. OEE, of course is the popular abbreviation for Overall Equipment Effectiveness—a sum of ratios that places a numerical value on “true” productivity. I’ve always harbored some reservations about OEE, especially as a comparative metric, because of the inherent variability of inputs. Automated data collection and modern data base analytics are a solution.

A press release and email conversation with Parsec came my way this week. It sets the stage by pointing to the pressure to increase quality and quantity, while reducing costs, leading manufacturers to seek a deeper understanding of trends and patterns and new ways to drive efficiency. The very nature of OEE is to identify the percentage of manufacturing time that is truly productive. It is the key metric for measuring the performance of an operation, but many companies measure it incorrectly, or don’t measure it at all.

In the latest example of its efforts to help manufacturers maximize performance while reducing costs and complexity, Parsec launched its real-time Overall Equipment Effectiveness (OEE) Performance Management solution.

Most OEE measurement systems capture data from a single source and offer reports that may be visually appealing but actually contain very little substance. Other OEE systems capture lots of data but fail to give operators the necessary tools to act on that data. The TrakSYS OEE Performance Management solution collects and aggregates data from multiple sources, leveraging existing assets, resources and infrastructure, and provides insight into areas of the operation that need improvement with the tools to take action.

“We are challenging manufacturers to go beyond OEE measurement and to begin thinking about performance management,” said Gregory Newman, Parsec vice president of marketing. “Our TrakSYS OEE Performance Management solution pinpoints the root causes of poor performance and closes the loop by providing actionable intelligence and the tools necessary to fix the bottlenecks and improve productivity.”


The Power to Perform

When designing the TrakSYS OEE Performance Management solution, Parsec took into account three key criteria for measuring OEE: Availability, Performance and Quality. Availability, or downtime loss, encompasses changeovers, sanitation/cleaning, breakdowns, startup/shutdown, facility problems, etc. Performance, or speed loss, includes running a production system at a speed lower than the theoretical run rate, and short stop failures such as jams and overloads. Quality, or defect loss, is defined as production and startup rejects, process defects, reduction in yield, and products that need to be reworked to conform to quality standards. As part of the solution, Parsec created a variety of standard dashboards and reports as well as the ability to customize reports through powerful web-based configuration tools.

“Our goal is to empower manufacturers to unlock unseen potential with their existing infrastructure,” added Newman. “Even small tweaks can save a plant millions of dollars each year.”

TrakSYS is an integrated platform that contains all of the functionality of a full manufacturing execution system (MES) in one package. The modular nature of TrakSYS brings flexibility to deploy only the functions that are required, without a major software upgrade. TrakSYS business solutions include OEE, SPC, e-records, maintenance, traceability, workflow, batch processing, sustainability, labor, and more.

What Is Smart Manufacturing and Why We Care

IDC Smart Mfg Info Graphic

[Updated: 1/28/15]

Last week I attended the board meeting of the Smart Manufacturing Leadership Coalition. Sometimes I’m an idealist working with organizations that I think have the potential to make things better for engineers, managers, and manufacturers in general. I derive no income from them, but sometimes you need to give back to the cause. SMLC is one of those organizations. MESA, OMAC, ISA, CSIA, and MIMOSA are other organizations that I’ve either given a platform to or to whom I have dedicated many hours to help get their message out.

In the area of weird coincidence, just as I was preparing to leave the SMLC meeting there came across my computer a press release from an analyst firm called IDC IDC Manufacturing Insights also about smart manufacturing. This British firm that is establishing an American foothold first came to my attention several years ago with a research report on adoption of fieldbuses.

The model is the “Why, What, Who, and How of Smart Manufacturing.” See the image for more information. I find this model interesting. As a student of philosophy, I’m intrigued by the four-part Yin-Yang motif. But as a manufacturing model, I find it somewhat lacking.

IDC insight

According to Robert Parker, group vice president at IDC Manufacturing Insights, “Smart manufacturing programs can deliver financial benefits that are tangible and auditable. More importantly, smart manufacturing transitions the production function from one that is capacity centric to one that is capability centric — able to serve global markets and discerning customers.” A new IDC Manufacturing Insights report, IDC PlanScape: Smart Manufacturing – The Path to the Future Factory (Doc #MI253612), uses the IDC PlanScape methodology to provide the framework for a business strategy related to investment in smart manufacturing.

Parker continues, “Smart manufacturing programs can deliver financial benefits that are tangible and auditable. More importantly, smart manufacturing transitions the production function from one that is capacity centric to one that is capability centric — able to serve global markets and discerning customers.”

The press release adds, “At its core, smart manufacturing is the convergence of data acquisition, analytics, and automated control to improve the overall effectiveness of a company’s factory network.”

Smart manufacturing

This “smart” term is getting thrown around quite a bit. A group of people from academia, manufacturing, and suppliers began discussing “smart manufacturing” in 2010 and incorporated the “Smart Manufacturing Leadership Coalition” in 2012. I attended a meeting for the first time in early 2013.

Early on, SMLC agreed that “the next step change in U.S. manufacturing productivity would come from a broader use of modeling and simulation technology throughout the manufacturing process”.

Another group, this one from Germany with the sponsorship of the German Federal government, is known as Industry 4.0, or the 4th generation of industry. At times its spokespeople discuss the “smart factory.” This group is also investigating the use of modeling and simulation. However, the two groups take somewhat different paths to, hopefully, a similar destination—more effective and profitable manufacturing systems.

Key findings from IDC:

  • Use the overall equipment effectiveness (OEE) equation to understand the potential benefits, and tie those benefits to financial metrics such as revenue, costs, and asset levels to justify investment.
  • Broaden the OEE beyond individual pieces of equipment to look at the overall impact on product lines, factories, and the whole network of production facilities.
  • Technology investment can be separated into capabilities related to connectivity, data acquisition, analytics, and actuation.
  • A unifying architecture is required to bring the technology pieces together.
  • Move toward an integrated governance model that incorporates both operation technology (OT) and information technology (IT) resources.
  • Choose an investment cadence based on the level of executive support for smart manufacturing.

Gary’s view

I’ve told you my affiliations, although I am not a spokesman for any of them. Any views are my own.

So, here is my take on this report. This is not meant to blast IDC. They have developed a model that they can take to clients to discuss manufacturing strategies. I’m sure that some good would come out of that—at least if executives at the company take the direction seriously and actually back good manufacturing. However, the ideas started my thought process.

Following are some ideas that I’ve worked with and developed over the past few years.

  • To begin (picky point), I wish they had picked another name in order to avoid confusion over what “smart manufacturing” is.
  • While there are a lot of good points within their model, I’d suggest looking beyond just OEE. That is a nice metric, but it is often too open to vagaries in definition and data collection at the source.
  • Many companies, indeed, are working toward that IT/OT convergence—and much has been done. Cisco, for example, partners with many automation suppliers.
  • SMLC is working on a comprehensive framework and platform (also check out the Smart Manufacturing blog). Meanwhile, I’d also reference the work of MIMOSA (OpenO&M and the Oil & Gas Interoperability Pilot see here and here).
  • I’d suggest that IDC take a look into modeling, simulation, and cyber-physical systems. There is also much work being done on “systems of systems” that bring in standards and systems that already exist to a higher order system.

I have not built a model, but I’d look carefully into dataflows and workflows. Can we use standards that already exist to move data from design to operations and maintenance? Can we define workflows—even going outside the plant into the supply chain? Several companies are doing some really good work on analytics and visualization that must be incorporated.

The future looks to be comprised of building models from the immense amounts of data we’re collecting and then simulating scenarios before applying new strategies. Then iterating. So, I’d propose companies thinking about their larger processes (ISA 95 can be a great start) and start building.

These thoughts are a main theme of this blog. Look for more developments in future posts.

Automation Company Touts PackML

Automation Company Touts PackML

Schneider Electric LogoI decided not to attend this year’s PackExpo although it is in Chicago. I had to draw the travel time/dollar budget somewhere.

However, there was an interesting session yesterday. Niels Andersen, Schneider Electric’s vice president of global industry solutions, showed attendees how to benefit from packaging standards without replacing existing PLCs.

During the presentation, end users and OEMs, including CPG customers and machine builders, will learn how to implement the Organization for Machine Automation and Control (OMAC) PackML standard and achieve OEE functionality without having to rip and replace existing automation infrastructure. The solutions and techniques discussed propose to help end users reduce the cost of integration while allowing for continuous performance monitoring and improving overall equipment effectiveness.

“The OMAC PackML standard, traditionally implemented in a PLC, proposes a common way to represent machine status through a defined interface, which is essential for downtime analysis and OEE calculations,” Andersen said. “But not all PLCs have the necessary memory, CPU or communication capabilities to accommodate the standard. Therefore many CPG and OEM customers need new, easy-to-implement advanced solutions and techniques as an alternative to replacing their existing controllers. This presentation will explain what those alternatives are.”