Modern Machine Shop article highlights Memex’s productivity partnership with Caron Engineering

Proactive Investors – September 29, 2014

Memex Automation (CVE:OEE) says its MERLIN product which works to improve manufacturing efficiency has been profiled in the September issue of Modern Machine Shop, alongside Caron Engineering’s adaptive control manufacturing methods.

The article describes Caron Engineering’s five multi-axis adaptive control machining methodologies and MERLIN’s ability to monetize the improved processes in real-time, said Memex.

The MERLIN device monitors production and capacity utilization on the shop floor, improving profitability, reducing waste and ensuring compliance with regulations. It enables customers to address production bottlenecks as they happen, converting idle time back into production and ultimately improving throughput and increasing income from plant operations.

MERLIN is highlighted in the article as improving production within and outside of the machining envelope by calculating capacity utilization plant-wide, through the measurement of overall equipment effectiveness. As a result, MERLIN gets “the Caron voice of process and the plant’s capacity utilization data” to the engineering and management teams in their respective business intelligence tools, on any device, the company said.

“With Caron and MERLIN, manufacturers can understand plant capacity in real-time, down to the accelerometers measuring vibration in spindle bearings, servo-drives and other machine components that can adversely affect cutting conditions, by the second,” said chief executive officer of Memex, David McPhail.

“Literally, MERLIN and Caron deliver the equivalent of the holy grail of manufacturing in a way that generates up to 400% IRR.”

Memex’s product was recently described in a case study by Mazak, which said that Merlin-related efforts to reduce downtime yielded a 42 percent improvement in utilization for the monitored machines.

In addition, Mazak also reduced operator downtime by 100 hours per month, while 400 hours per month of previously outsourced work was returned to the company.

To see the full article, please click here.

Memex says clients regularly claim IRRs of more than 400% using MERLIN

Proactive Investors – September 26, 2014

Memex Automation (CVE:OEE) says its MERLIN product which works to improve manufacturing efficiency has been featured in the September issue of PLANT magazine.

The cover article of the issue describes how Canadian manufacturers can eradicate the productivity gap with MERLIN, said Memex.

The hardware and software solution generates up to a 400 percent IRR upon installation in manufacturing plants, according to the company, and is featured in the article alongside Google‘s $3.2 billion purchase of Nest as well as Apple‘s, Samsung’s and Sony‘s “internet of everything consumer-based wearables.”

The Merlin device monitors production and capacity utilization on the shop floor, improving profitability, reducing waste and ensuring compliance with regulations. It enables customers to address production bottlenecks as they happen, converting idle time back into production and ultimately improving throughput and increasing income from plant operations.

The company’s product was recently described in a case study by Mazak, which said that Merlin-related efforts to reduce downtime yielded a 42 percent improvement in utilization for the monitored machines. In addition, Mazak also reduced operator downtime by 100 hours per month, while 400 hours per month of previously outsourced work was returned to the company.

“Our clients regularly detail to us IRRs of more than 400% because they’re using our solution to connect their plants to their management teams in real-time,” said CEO of Memex David McPhail.

“This Plant article is spot on the money because it describes how Canadian manufacturers can move from the disconnected to the connected manufacturing environment; eradicate the Canadian productivity gap; uncover the hidden plant; and, generate more production and income from operations using the same labour and equipment.

“That’s how these IRRs are generated,” he added.

To see the full article, please click here.

To read the PLANT magazine article in full, please click here.

Tool Monitoring for Multitasking Machines

Modern Machine Shop – September 26, 2014

Machine tools designed to combine milling, turning and other metalworking processes have remarkable potential for efficiency and productivity. Completing parts in one pass across a multitasking machine streamlines production by eliminating multiple setups, avoiding errors when parts are refixtured and performing several operations simultaneously. Multitasking machines also are well-suited for running unattended or having one operator oversee multiple units.

By their nature, multitasking machines tend to be complex and sometimes difficult to understand, however. They follow a variety of configurations—mills with turning, lathes with milling, twin-spindle machining centers and three-turret lathes are a few examples. Additional axis motions such as a rotating milling head (B axis) and turrets on a cross-slide (Y axis) compound this complexity.

And multitasking machines impose distinct challenges to cutting tool usage and management. For example, multitasking machines may have a limited number of stations for cutting tools on the tool turret or automatic toolchanger. Certain cutting tools may be called upon for both milling and turning operations. A worn or broken tool that interrupts a multitasking machine may have the same effect on productivity as unplanned downtime on two or more single-purpose machines.

Systems designed to monitor a tool’s condition, adjust automatically for wear and capture information about the tool’s performance can be especially valuable on multitasking machines. One of the biggest challenges to tool monitoring on a multitasking machine is coping with simultaneous cutting operations.  One system designed specifically to meet this challenge is TMAC-MP from Caron Engineering (Wells, Maine) which stands for Tool Monitoring Adaptive Control for Multi-Process machines.

This system, which includes sensors installed on the machine tool and software installed on the CNC unit, monitors tool performance to detect wear or breakage, automatically adjusts feed rates to compensate for wear (adaptive control), and captures data about tool life. Several tools cutting at the same time can be monitored and controlled equally well, with all data recorded and displayed in a centralized interface. Data from a TMAC-MP system on an individual machine can be transmitted to a shop-wide machine monitoring system, enabling managers to incorporate critical tool data into calculations of overall equipment efficiency.

A Multi-Processing Extension

TMAC-MP is an extension of Caron Engineering’s pioneering TMAC tool monitoring system. It is based on the principle that a machine tool has to work harder to maintain a set feed rate as the edges of a cutting tool grow dull. In other words, spindle horsepower gradually increases as wear occurs. By sensing spindle horsepower output, the system can detect if a cutting tool is worn or broken.

More importantly, the system can be set to react to changes in the horsepower readings. If the power monitor detects evidence of excessive wear, it can signal the machine control to issue an alarm, initiate a tool change to retrieve a fresh spare tool or stop the machining process altogether.

The adaptive control option enables the control to automatically adjust the feed rate to maintain a constant horsepower rating as the tool undergoes normal wear patterns. As a result, the cutting tool performs at its optimum power level, thus extending its life, reducing cycle time, and avoiding stress on the spindle bearings and other machine components. Under this protocol, feed-rate adjustments are made constantly in small increments (typically 1 percent of the programmed feed rate) for a smooth transition that further protects the tool and workpiece surface.

For both monitoring and automatic adjustment, the system’s software can “learn” the normal horsepower draw for a given tool and operation while the tool is cutting. Using this baseline, the user can set limits and establish the preferred response.

The multi-processing enhancement of the system is designed to perform these functions even when multiple tools are cutting at the same time. Essentially, the software was reformatted to be multitasking in its own right. For example, this development enables the system to monitor and control two turning tools cutting simultaneously in an upper and lower turret while a milling tool is doing end work on a part in the subspindle.

Originally developed for a Tsugami Swiss-type lathe and introduced at IMTS 2012, TMAC-MP also includes significant hardware innovations. Most important is the ability to monitor very small tools such 0.004-inch- (0.1-mm-) diameter drills. To this end, Caron Engineering had to develop new strain sensors that can be fully embedded in static toolholders sized for tools this small. The company also developed three-axis and single-axis accelerometers for measuring vibration. Mounted on the spindle or tooling slide, these sensors record vibration in spindle bearings, servodrives and other machine components that can adversely affect cutting conditions.

The system’s user interface was also changed so that machine and cutting tool data can be viewed in a bar graph that shows tool condition and remaining tool life for all tools being monitored. This information can be archived in any structured query language (SQL) database. The software can also be set up to send alarms by email or transmit them as text messages.

The Larger Connection

As valuable as tool monitoring and adaptive control may be for the individual multitasking machine, Rob Caron, president and founder of Caron Engineering, believes that the ability to port data across a network is the most substantial pay off awaiting shops and plants that implement the TMAC-MP system.

“Making tool data available to third-party software applications such as shopfloor machine monitoring opens doors to many possibilities such as plant-wide, data-driven decision-making and integrated automation,” Mr. Caron says. As a first step in this direction, his company is partnering with Memex Automation (Burlington, Ontario).

Memex’s manufacturing execution system, Manufacturing Execution Real-time Lean Information Network (MERLIN) supplies OEE metrics to support performance, productivity and profitability initiatives. The system tracks manufacturing operations bi-directionally from the ERP work order to each machine’s operations. MERLIN connects to all machines on the shop floor using various protocols, MTConnect adapters and/or network conductivity devices.

According to Mr. Caron, TMAC-MP users can use MERLIN’s interface and connectivity to deliver in-machine metrics from the shop floor to the operations and corporate executives, even to mobile devices or other web-enabled systems.

This connection also has the benefit of validating the productivity and efficiency gains delivered by multitasking machine tools, as well as making those machining resources more secure by detecting and preventing cutting-tool-based constraints to their full potential. “Multitasking machines and tool monitoring are more than complementary technologies. They are mutually empowering,” Mr. Caron concludes.

To see the full article, please click here.

The Internet of Everything

Plant Magazine – September 25, 2014

When Google purchased Nest Labs Inc. for $3.2 billion in January, the internet giant was buying more than a company that manufactured “smart” thermostats and smoke detectors – it was buying a position in the race to digitize people’s homes.

The thermostats learn how inhabitants like their homes to be heated and cooled, and then automatically adjust the temperature.

Google certainly has the bankroll to hedge bets on deals like the one with Nest, a fairly new company that grew fast. Co-founded in 2010 by two former Apple engineers, the company had more than 130 employees by the end of 2012 and now analysts at Morgan Stanley estimate it’s selling 100,000 thermostats a month. At $250 each, annual revenue is expected to top $300 million. That’s a drop in the bucket when you consider Google has more than $60 billion in revenue, but it’s money that can be used to develop a suite of smart home products including locks, doorbells, baby monitors and humidity monitors, all packed with sensors that capture user information and a wi-fi chip to relay the data.

Nest’s “smart” innovations are a prime example of the capabilities home automation and “connected” technologies are playing in the current consumer market place. Other technology giants, including Apple, Samsung and Sony, are developing wearable devices such as watches and smartbands that collect data about users’ activities and provide them with details such as how many steps they’ve taken in a day or how many calories they burned on a weekend bike ride.

Now thanks to this growth in the consumer market, costs of sensors, controllers and communications have dropped, and connected devices are making a big splash in business.

A sector that will truly benefit is manufacturing.

Intelligent sensors, cameras and tracking devices are transforming how companies operate and changing how businesses use data. The basis of what’s called “Industry 4.0” builds on the fundamentals of its first, second and third iterations. But it also takes mechanical and mass production, and the electronics and control systems of today to a new level where manufacturing is driven by machine-to-machine (M2M), person-to-machine (P2M), and person-to-person (P2P) connections within the Internet of Everything (IoE, a.k.a Internet of Things).

It connects everything from industrial equipment and systems to the internet via wireless and wired networks to gather and transmit data that manufacturers use to improve efficiency, productivity, asset health, quality, safety and environmental impact.

Big money, big possibilities According to research conducted by General Electric, enabling internet-connected machines could add up to $15 trillion to global GDP by boosting annual productivity growth by 1% to 1.5% in the US.

“It’s extremely important that we explore the potential of connectivity, says Victor Woo, general manager for IoE at Cisco Canada. “We’re gaining intelligence from dark assets, such as machines and other systems that will help businesses make better decisions.”

A report for Cisco by Lopez Research suggests as costs decrease for standard “smart” sensors with IP communications and embedded controls, solutions will be implemented across manufacturing equipment and into new areas that have not seen much investment in automation, such as Balance of Plant equipment and supply logistics. The benefit for manufacturers comes from the information collected by these sensors that’s communicated back to shopfloor workers, plant managers and software systems. Although in its infancy, IoE is already having an impact, and manufacturers are reaping the benefits. Some of the world’s largest industrial players are leading adoption, including Cisco, General Electric, General Motors, Toyota, Samsung, Intel and Dell.

A forecast prepared by IT research firm IDC Canada and telecommunications company Telus Corp. suggests companies are preparing to increase their spending on data collection and analysis, the beginning of a rapid industrial-scale innovation that will have far reaching implications.

IDC estimates Canadian companies will spend $21 billion on such projects in 2018, up from $5.6 billion last year – a 375% increase. About 13% of study respondents were already working in the IoE, while another 30% say they are planning to adopt the technology within two years.

The survey suggests advancements in the reach and speed of wireless networks and technologies such as cloud computing are fuelling growth for IoE and opening up its potential for manufacturing.

Connecting machines creates intelligent networks along the entire value chain that communicate and control each other autonomously with significantly reduced intervention from operators. Machines predict failure and trigger maintenance processes autonomously, while self-organized logistics would react to unexpected changes in production, such as materials shortages and bottlenecks.

“IoE can not only increase productivity, it enables entirely new business models. Companies need to examine its possibilities as a competitive advantage or they risk falling behind global innovators already utilizing new applications to creatively reinvent their businesses,” says Tony Olvet, group vice-president of research at IDC Canada.

Equipping people with mobile technology, you dramatically shrink the delta between when a problem occurs and when it’s acted upon, says Mark Bernardo, general manager of automation software for GE Intelligent Platforms, in the Cisco study.

“If there’s a quality control problem in a production line, they can shut down the line before it continues to create products that will all be waste.”

For example, Harley Davidson installed software at it’s York, Pa. plant that records how different equipment is performing, such as the speeds of the fans in its painting booth. Software automatically adjusts machinery if it detects a measurement, such as fan speed, temperature or humidity, has deviated from acceptable ranges.

General Motors has implemented a standards-based network architecture called the Plant Floor Controls Network. It standardizes the design of each of its plant networks to establish a single engineering team that monitors and troubleshoots network operations globally. The automaker has since reduced network downtime by 70%.

And at a General Electric plant in Schenectady, NY, tens of thousands of miniature sensors are collecting data about each step in the manufacturing of batteries. The sensors know information relating to humidity on the shop floor and how much pressure each machine must apply to particular battery components. The company says it’s using the data to improve its factories by determining which conditions are associated with the best products.

Meanwhile, Cisco Canada is in the process of opening an IoE Innovation Centre in Toronto, one of four locations around the world, where it expects to spend $100 million over the next 10 years on the development of infrastructure and technology. “Convergence is the key work here,” says Woo. “We have to bridge information within the business by connecting the shopfloor to the top floor.”

Woo, looking at Cisco research, estimates that IoE will drive net profits of $3.9 trillion in the global manufacturing sector alone over the next 10 years. Canada’s share would be about $100 billion.

He contends manufacturing has the most to gain from IoE globally.

Leveraging value While sensors and computerized automation have been around for decades, PLC and PC-based controllers and management systems are largely disconnected from IT and operational systems. They’re organized in a hierarchal fashion within individual data silos that often lack connections to internal systems.

But Dave McPhail, the CEO of Memex Automation in Burlington, Ont., says that’s changing thanks to IoE.

“Having the ability to connect equipment via ethernet is providing businesses with a new value stream based on the fact that you can pull data in a cost effective way,” he says.

Memex develops real-time shop-floor-to-top-floor technologies, and its flagship product MERLIN provides overall equipment effectiveness (OEE) metrics in real-time to allow manufacturers to enhance their production through shop-floor data analysis.

The company has strategic partnerships with Microsoft and tool builder Mazak, which has installed the MERLIN OEE system at its plant in Florence, Ky.

Thanks to new sensor information, wireless connectivity and big data processing tools like Memex’s, IoE would help manufacturers improve OEE by gathering information related to equipment health to minimize machines failures.

The next step in IoE development, McPhail says, is a ubiquitous platform.

“We have the hardware part figured out. Now we need an open source protocol that allows data to be consumed by any number of applications to add even more value, such as overall equipment effectiveness, total predictive maintenance and the cost of core performance,” he says. “I think we’ve only scratched the surface in terms of how we can use data. Our imagination is our only limitation.”

So you want to enter the IoE realm? A Cisco research paper suggests there are four elements that provide the foundation for smart manufacturing within IoE:

Network. “Smart” manufacturing environments require a standardized IP-centric network that enables all devices within a plant to communicate to operational and enterprise business systems. A standard IP network also makes it easy to connect and collaborate with suppliers and customers to improve supply chain visibility.

Security. Safeguards must be built into any solution, including security procedures such as hardware encryption, physical building security and network security for data in transit.

Software systems. Systems must translate information from the physical world into actionable insight that humans and machines can use. For example, Toyota is using Rockwell Automation software for real-time error corrections at its Alabama plant to minimize rework and scrap rates. The software is saving the automaker $550,000 annually.

Big data and analytics. Processing tools are enabling real-time data stream analysis that provides dramatic improvement in problem solving and cost avoidance.

Smarter manufacturing may only have scratched the surface of the Internet of Everything, but sooner rather than later, the sector will leverage the age of the machines, and unlike James Cameron’s Skynet (artificial intelligence run amok) in the Terminator movie series, that’s a good thing.

This article appears in the September 2014 issue of PLANT.

To see the full article, please click here.

CNC Hardware Adapters Connect All Legacy Machines, No Matter the Make, Model or Vintage

Astrix Networks Inc., operating under the trade name Memex Automation Inc., is solving the “last meter of productivity challenge” with new CNC hardware solutions that utilize MTConnect, an open, royalty-free standard that is intended to foster greater interoperability between manufacturing devices and software applications.

For older FANUC-controlled machines that still populate about 50 percent of CNC machine shop floors, Memex Automation’s new Ax760–MTC is a fully configurable hardware adapter that allows you to communicate with your CNC’s utilizing the MTConnect standard.

The plug-and-play hardware connects into the main FANUC I/O Link bus to transform FANUC signal into the MTConnect software protocol without disrupting the machine. The result is a machine that can passively detect data, on both the X and Y addresses from 0.0 to 127.7, as well as 16 additional digital inputs, allowing Memex’s MERLIN (Manufacturing Enterprise Real-time Lean Information Network) software to track a large number of data inputs that measure Overall Equipment Effectiveness (OEE) in real-time, enterprise-wide, machine by machine and other operational machine information.

For any machine, the Ax9150 UMI-MTC is a fully configurable MTConnect hardware adapter that allows you to communicate with your CNC utilizing MTConnect. Rather than buying a new controller, you can enhance your oldest legacy controllers so they can take advantage of today’s MTConnect communication standard and take advantage of MERLIN OEE benefits. In many instances, this can substitute for a machine monitoring retrofit. The Ax9150 UMI-MTC offers simple installation regardless of CNC make, model, or type.

“Increasing the utilization of both legacy and new assets is critical to a modern company and MERLIN makes that happen,” said Dick Morley, who is on the Board of Memex Automation and is known as the “father” of the programmable logic controller (PLC).

To see the full article, please click here.