Saturday, September 17, 2022

Productivity Improvement Through Smart Machines

This topic falls under Facilities Industrial Engineering.


Jidoka - Automation and Mechanization - Process Engineering and Industrial Engineering in Toyota Production System

Jidoka, a pillar of Toyota Production Systems advocates automation with human touch in all operations of a process to increase productivity of operators as well as that of total systems.


IIOT, Industry 4.0, 4IR (Fourth industrial revolution) etc. are  frameworks to merge the operational technology (OT) with the information technology (IT) to provide new solutions for automating and networking industrial machines and systems for performance and productivity improvement.

What is a Smart Machine?

It is self-­aware, reacts autonomously and provides information about the product being produced, production parameters utilized, production time taken production quantity in unit time periods, production history,  configuration, condition, quality and Overall Equipment Efficiency (OEE) to other machines.

Smart Machine Control
Machine vision and advanced motion control are key components of smart automation. Engineers can increase throughput and build highly efficient modern machines that sharpen accuracy and easily adapt to new products and processes.

Today, the keys to smart machine control are gaining insight into the machine’s operation and the ability to adjust control outputs. Engineers rely on sensor information to monitor the condition of mechanical parts, which gives them the ability to observe the process for quality control or closed-control loops for applications like force feedback or precise positioning.

Today, LabVIEW (of NI.Com) graphical programming helps leading machine builders master this increasing system complexity with add-on modules for motion control, machine vision, and control design and simulation.

"We define smart machines as digitized (or cyber-physical) machines that consist of physical components (e.g., machine frame, engine, and tools), intelligent components (e.g., sensors or software that enable sensing, collecting, and storing of data), connectivity components (allowing for the interaction with the environment and the processing of data outside the machine; e.g., in the cloud), and are extended by machine-related services (e.g., services focused on optimizing manufacturing processes). - Philipp Scharfe and Martin Wiener, Technische Universität Dresden.



Smart Machines - Illustrations


2022


Smart Textile  Machinery 


PLEVA  StraightLiner SL smart


High-tech Automatic Straightening Machine

The heart of the SL smart system is the well-established advanced traversing camera 
technology which is unique in weft-straightening. The universal high-resolution camera 
captures up to 20 measuring points per meter of fabric width. Advanced evaluation 
algorithms enable an ultra-precise distortion analysis which enables perfect straightening 
results in a blink of time.

To further enhance the efficiency of your processes, a modular control system (PLEVATEC 
smart) can be directly integrated into the machine. This allows to measure, control, 
visualize, and protocol the critical parameters of your specific process, for instance:
• Exhaust humidity (FSX) 
• Fabric temperature (TDS)
• Pick/course density (CAM)
• Residual moisture (RR/RF 120)

CAMERA SYSTEM

Universal high-resolution camera for easy 
detection of a huge variety of fabrics
 • Image capturing in 0.00001 seconds
 • Picture size standard: 40 x 30 mm
 • Reflecting lighting
 • High-speed analysis >10 times per second
 • Picture analysis independent of fabric
speed. From stand still up to fabric speeds 
of 600 m/min.

Smart image processing 
• Universal, self-optimizing detection
• Horizontal distortion
• Brightness control
• Advanced, self-made digital signal processing
• Horizontal density (picks/courses) (option)
• Vertical density (warp/wales) (option)

VISUALIZATION AND CONTROL

High performance, intuitive user interface

The newly designed user interface provides an overview of the most important information 
such as all relevant measuring values, tolerances and status information. 
The high-performance 12“ HMI touch panel can withstand surrounding temperatures of up 
to 60°C without cooling and is suited for the roughest working environments.

Realistic representation of the running fabric

VISUALIZATION AND CONTROL
• Easy to use, intuitive user interface for operator
• Extremely robust 12" HMI touch panel
• Modular concept for upgrades
Modular overview of controls
Status information bar
Current values with tolerance indication 
Trend and visual representation

Controls with status
The newly designed user interface provides an overview of the most important information 
such as all relevant measuring values, tolerances and status information. 

The high-performance 12“ HMI touch panel can withstand surrounding temperatures of up 
to 60°C without cooling and is suited for the roughest working environments.

Realistic representation of the running fabric

 Fabric distortion from selvedge to  selvedge
 Integrated measurement  of fabric width
 Indication of fabric position relatively to center
Max. possible fabric width in machine

FEATURES OF PRODUCT

• Direct readout of skew and bow in % and mm/inch
• Integrated width display in mm/inch
• Indication of fabric position in mm/inch
• Visual representation of the actual running fabric

To ensure that the process is running smoothly and every running meter of fabric is 
produced in the desired quality, different trends are provided. Additional trends for 
comparing skew/bow and the position of the skew-/bow-rollers are also directly available. 
Furthermore, the integrated recipe management provides a database for all critical setvalues, tolerances, controller pre-sets, detection parameters, etc.. This allows the highest 
level of reproducibility for different products and enables easy operation.

To maximize the capabilities of the SL smart, several current connection standards are 
supported and connection to several Industry 4.0 applications can be realized. Connections 
to production lines, MES- and ERP-systems can be realized through:
• ProfiNet or ProfiBus (option)
• OPC UA (option)
• CSV files (option)
For a state of the art instant service of the straightening machine, an industrial router 
can be provided for remote access and service. This can help to further maximize the 
availability and performance of the SL smart.
https://www.pleva.org/fileadmin/pleva/Public/Content/Images/Content/PDFs/Prospekt_SL_smart.pdf

https://www.pleva.org/en/straightliner-textile-production-woven-knitted-goods.html

AK-DSL 2018 machine

AK Dyeing presented AK-DSL 2018 machine,  has washing-smart wash system and hybrid technology to reduce 30%-40% wastewater discharge. Sensor (steam, water, electric consumption, machine run speed, chemical injection rate, Fabric run speed) are all embedded in the machine to provide digital operation data. All the operational data collected through the sensors can be stored in the Industrial PC provided and connect to the Dyehouse’s Central Management System.

Sensors and Controls for Textile Machinery


Smart knitting to change the world
https://www.knittingtradejournal.com/sponsored-content/14631-smart-thinking-to-change-the-world

Application of Sensor Technology in Textiles
https://textilelearner.net/sensor-technology-in-textile-industry/

Monforts Industry 4.0 Innovations



Qualitex 800 control system,  along with the Web-UI app, allows the remote visualisation of Monforts technologies via smart phones and tablet devices. Resource efficiency is being addressed via the latest technologies such as the company’s Eco Line for denim, based on two key technology advances – the Eco Applicator for minimum application of the selected finishing chemicals and the ThermoStretch. In many textile mills globally, the cost of energy for running integrated manufacturing lines – especially those for fabric finishing that can involve numerous sequences of heating and subsequent drying – is now eclipsing the cost of paying people to operate them. The ability of the Eco Applicator to significantly reduce energy costs has seen it rapidly accepted on the market.
https://www.indiantextilemagazine.in/smart-dyeing-finishing-chtc-fongs-innovations/

Creating the Digital Textile Factory at Oerlikon Manmade Fibers 


Oerlikon Manmade Fibers, the world market leader in textile machine manufacturing for manmade fibers, based in Germany, shares  a glimpse of the company's OpenStack-based edge computing architecture and how it is making possible the digitalization of the “From Melt to Yarn, Fibers and Nonwovens” process chain (Video presentation). Oerlikon is innovating heavily in the fields of automation, machine learning and process integration towards the vision of the fully digitalized smart textile factory

Oerlikon’s Smart Factory helps eliminate waste
The intelligent factory is no longer a vision, it has long become reality. Digital solutions have become fixed elements of Oerlikon’s products and services.



Grinding wheel system
Abstract
A grinding wheel system includes a grinding wheel with at least one embedded sensor. The system also includes an adapter disk containing electronics that process signals produced by each embedded sensor and that transmits sensor information to a data processing platform for further processing of the transmitted information.
Patent: US20030194946A1
United States
2006-01-10 Publication of US6985791B2
2006-01-10 Application granted

Grinding wheel having grinding monitoring and automatic wheel balance control functions
EP0460282B1
European Patent Office

It is also proposed to provide an acoustic-wave sensor (AE sensor) for detecting high-frequency ultrasonic vibrations (acoustic or elastic emissions) which are generated by the grinding wheel, as disclosed in Publication No. 64-278 of examined Japanese Utility Model Application. The disclosed AE sensor is fixed to a stationary member of the grinding machine, for detecting vibrations which are transmitted through a liquid that is jetted on a side surface of the abrasive portion of the grinding wheel. In this case, the vibrations detected by the sensor may be affected by the conditions in which the liquid is jetted against the abrasive portion, or by gases which are present in the liquid.
[0007]
Conventionally, a temperature sensor is embedded in the workpiece to be ground by the grinding wheel, so as to measure a temperature at the grinding surface of the wheel during the grinding operation. However, the known sensor is not able to accurately measure the wheel temperature since the workpiece having the sensor is moved relative to the rotating wheel during the grinding operation. If the vibrations or the wheel temperature cannot be accurately detected as in the conventional grinding machine, it is difficult to determine abnormalities in the grinding, resulting in increased unacceptance or reject ratio of the ground workpieces. Further, the above manner of measuring the wheel temperature is restricted by the manner of grinding and the configuration of the workpiece. For example, it is difficult to embed the temperature sensor in a cylindrical workpiece which is rotated during the grinding operation.

1995-07-26 Application granted
1995-07-26 Publication of EP0460282B1

Sound Sensors Smooth Grinding Operations
Departments - Reference Guide
Acoustic emission sensing revolutionizes the landing gear strut surface smoothing process.
October 10, 2013

HWANCHEON SMART MACHINING CENTER

For Graphite Machining
With SMART-UaX, easy set up of the machine to get the best and fastest machining result with just four botton presses.

SKU: SMART-UaX
Categories: SMART MACHINES

Product Smartness
Generation of optimized NC data
NC data is generated and sent automatically from CAD system. If a problem occurs during machining unattended machining is achieved by automatically analyzing and editing NC programs.

Automatic tool process control
The process step-by-step tool checks status and pre-correction to prevent breakage and abrasion due to processing errors. Each material is processed per hourly forecasts, records and time check by usage, life cycle management to be ready for the next process.

Workpiece automatic detection
Automatic detection of size and position of the workpiece. Prevent the pre-processing error to minimize non-cutting time. The defective material is marked automatically by detecting the H-SMART analysis after shape is compared to stop the process.

Product Specifications
Additional information
Swing Over Bed [mm]
1,300 / 750 / 420

Max. Cutting Diameter [mm]
20 / 20 / 20

Working Surface [mm]
1,200 x 700

Table Loading Capacity [kg]
400

Max. Spindle Speed [rpm]
12,000 (opt. 20,000)

Spindle Motor [kW]
18.5 / 11

Type of Tool Shank
BT-40 (Option : BBT-40, HSK-A63)

Tool Storage Capacity [ea]
50

Floor Space (Length X Width) mm
3,130 x 5,308

NC Controller
H-SMART

Smart Machine Accessory - iQsmartgrind - Hardware and Software for  Process Analysis of  Spring End Grinding

2021

 Creating machines from the ground up that optimize productivity, quality, and safety, while providing insights and information to decision makers when it’s needed is a requirement of best-in-class manufacturers.
Solutions for Smart Machines and Smart Factories by Rockwell Automation.

Global $210+ Billion Smart Machine Technology and Markets to 2026: Autonomous Robots to Account for $164.9 Billion / Intelligent Assistants to Account for $26.2 Billion
September 15, 2021 

Smartification in the Mechanical Engineering Industry: A Typology of Smart Machines
August 2021
Conference: Americas Conference on Information Systems (AMCIS)At: Montreal.
Philipp Scharfe and Martin Wiener, Technische Universität Dresden.

Global Smart Machines Market 2021-2026 - Integration of Robotics, AI and IoT a Substantial Smart Machine Market Opportunity for Service Automation - ResearchAndMarkets.com
February 17, 2021 
Smart machines collectively represent intelligent devices, machinery, equipment, and embedded automation software that perform repetitive tasks and solve complex problems autonomously. Along with AI, IoT connectivity, and M2M communications, smart machines are a key component of smart systems, which include many emerging technologies such as smart dust, neurocomputing, and advanced robotics. Smart machines will also benefit significantly from advancements in the convergence of AI and IoT, also known as the artificial intelligence of things (AIoT).

Select Research Findings

The global smart machine market will reach $29.9 billion by 2026
Cognitive technologies in North America market will reach $1.43 billion by 2026
Autonomous robots will reach $9.5 billion globally by 2026, growing a CAGR of 18.6%
Neurocomputing solutions for smart machines will reach $1.8 billion globally by 2026



2020
Jan-June 2020


Smart Machine Tool Digital Engineering - Boost 4.0boost40.eu - PDF
Jan 2, 2020 - “FILL will be the leader in smart machines building by reducing the development time of machines. The developed edge-technology based on smart engineering

Smart Machines Market Is Expected To Witness CAGR Of 19.3% During The Forecast Period (2019-2027)

Manufacturing Perfection: How to Make 3D Printing Machines Smarter and Reduce Defects
January 06, 2020


With each line of code and crunch of data, University of Virginia graduate engineering students Oliver Holzmond and Jamison Bartlett get a step closer to revolutionizing the way things are made.

Across several sprawling labs in the UVA School of Engineering’s departments of Mechanical and Aerospace Engineering and Materials Science and Engineering, Holzmond, Bartlett and their Ph.D. adviser, Professor Xiaodong “Chris” Li, are fine-tuning sensors and computer code that will analyze each layer of a 3-D-printed object, spot flaws, decide how to fix the flaws and direct the 3-D printer to make corrections.


2019

Jan - Mach 2019

Fanuc Smart Machine Control


Machine characteristics change over time due to variations in load, temperature, machine position, wear etc. Smart machine control is a set of features that improve various machine control functions. What makes these functions „smart“ is that they automatically adapt to changing machine conditions in real-time. Shortest cycle times, highest precision and machining quality can be achieved sustainably.

For instance, Smart Adaptive Control adapts the feed rate to the actual spindle load and temperature during roughing. By this, Smart Adaptive Control helps you to utilize the power of your machine tool and to reduce cycle time.

Another example is Smart Machining Point Control. The function predicts the movement of the machining point using a model and suppresses vibration. This reduces the position error. Smart Machining Point Control therefore improves the surface quality of machined parts.

https://www.fanuc.eu/sk/en/cnc/smart-machine-control


Smart Wrenches and the Future of Connected Tools
By Brian Ballard
September 15, 2017

Last year, GE Aviation began a pilot program at its facility near Cincinnati, Ohio. They sought an augmented reality solution that combined three technologies: a WiFi-enabled Atlas-Copco Saltus MWR-85TA torque wrench, Glass Enterprise Edition smart glasses, and Skylight augmented reality platform from Upskill.

Data provided by the smart wrench is integrated into AR user experience so that mechanics wearing Glass can get a real-time reading of exactly how many pounds of pressure to apply to the B-nuts that seal fluid lines and hoses from Skylight. A green reading shows when the torque is just right.


Smart Fault-Detection Machine for Ball-Bearing System with Chaotic Mapping Strategy
Sensors (Basel). 2019 May; 19(9): 2178
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6539469/

Wemp Smart CBD Vending Machine
Wemp is a CBD product distribution machine featuring the latest technologies. With its touch screen interface it has unlimited possibilities and it allows the sale of more than 80 different products 7 days a week, 365 days a year!
https://wempvending.com/

2017



Smart Pallets
Smart Pallets Help Achieve Scalable and Flexible Manufacturing
JULY 31, 2017
Shelby Township, Michigan-based Fori Automation Inc., a specialist in automatic conveying and handling systems, is modernizing the assembly line of a large U.S. automobile plant with rail guided carts, fail-safe Siemens SIMATIC S7-1200 controllers, and IWLAN.
https://www.totallyintegratedautomation.com/2017/07/smart-pallets-help-achieve-scalable-flexible-manufacturing/

Leonardo Smart Rotational Moulding Machine
http://www.leonardosmart.com/

Smart Machine
Bringing intelligence into the milling process is the intended aim of "smart machine".

Optimization of the Machining Process

http://www.gfms.com/country_US/en/Products/Milling/smart-machine/oss.html

Patented: The Original OSS
The intelligent Operator Support System optimises the machining process according to the specifications of the workpiece. The target variables – speed, accuracy and surface quality – as well as the workpiece weight and the complexity of the machining application can be selectively defined and modified at any time via an intuitive user interface.

Setting priorities
The user can define the machine settings via the OSS, depending on the operation. He can choose from 12 predefined settings or extend them as desired.

Priority: Time

Only the time is of interest when roughing. If the operator selects the time as the highest priority, then OSS extends the tolerance band. In addition to this, the control system adapts the speed profile to the geometry that is to be processed.

Priority: Surface quality

In order to maintain the best possible surface quality despite poor NC program quality, the tolerance band is enlarged and the transitions are smoothed

Priority: Accuracy

If the workpiece demands extremely high precision, the tolerance band selected is narrower, in order to achieve the required accuracy. The control system is configured in such a way that the best possible geometrical accuracy is guaranteed.

User-defined setting

Additional settings can be saved in a library and can then be used again at any time. Several positions can be selected between the extremes (surface quality, accuracy, time).

Productivity & Precision

Your benefit
The intelligent system sets the dynamic behaviour of the machine exactly according to the workpiece requirements
Shorter machining times
Better surface quality
Intuitive handling of complex settings
Reduced complexity when setting up a workpiece
http://www.gfms.com/country_US/en/Products/Milling/smart-machine.html

2016

Cat (Caterpillar) Connect Technology: Hardware and software available for equipment to arm customers with information designed to help them optimize their operations. Specific construction technologies include:

        o  LINK, a solution that captures vital performance and product health data and makes that data available on the web to guide decision-making.

        o  GRADE and COMPACT, two productivity solutions that help operators move material faster, more accurately and with fewer passes.

        o  PAYLOAD, an on-board system for trucks and loading tools that drives higher efficiency, shorter cycle times and lower cost per ton.

http://www.caterpillar.com/en/news/corporate-press-releases/h/caterpillar-introduces-the-age-of-smart-iron-digital-technology-designed-to-transform-productivity-efficiency-and-safety-on-job-sites.html

Smart Asphalt Compaction


______________

______________
Catpaving
Caterpillar’s new B-Series tandem vibratory asphalt roller models include a range of advancements in intelligent compaction technology to deliver higher quality compaction. These models — the CB64B, CB66B, and CB68B — feature technological improvements made possible through Cat Compaction Control, Caterpillar’s intelligent compaction suite. The suite consists of dual air-purged, infrared temperature sensors that are integrated into the front and rear of the machine.
http://www.government-fleet.com/channel/equipment/article/story/2016/02/caterpillar-rolls-toward-smarter-asphalt-compaction.aspx


2015

Smart Food Processing


A Cisco project involving Sugar Creek Packing Co. , Washington Court House, Ohio is making machines and processes smarter. The company recently commissioned a brownfield project in Cambridge City, Ind., Harvesting large amounts of data and feeding it back as actionable information is used for  for establishing a high-performance work team structure at the plant. “High-performance work teams are semi-autonomous teams work with little supervision, with production, maintenance and HR issues handled by team members. They need meaningful feedback and they get it from the smart features of the system. A sous vide cooking system is an illustration of it. It is a disruptive cooking technology and a highly automated system, with hundreds of sensors to control the process. To access the data, team members use a Cisco mobile app called Jabber, “essentially an IP phone. This feature substitutes installing the system based on ordinary mobiles with a booster system that would have added $300-500 million to project cost. Jabber radios essentially function like a desk phone and integrate easily with plant software. The wireless network also will track worker locations within one meter via RFID tags embedded on protective headgear.

http://www.foodprocessing.com/articles/2015/plant-automation/?start=0


2014

“Smart” ProSlab 155 Automated Turf Harvester

National Instruments Corporation, Austin, Texas describes the machine as smart machine.

The machine uses LabVIEW software and CompactRIO hardware supplied by National Instruments. The smart machine harvests turf 20 percent faster, and uses half the diesel fuel than other turf harvesting machines on the market. It uses more electric systems. FireFly engineers can also remotely monitor, diagnose, update (and control) the sensor-laden ProSlab 155

http://fireflyequipment.com/proslab-155/

http://sine.ni.com/cs/app/doc/p/id/cs-16758
________________

________________


2013

The technologies for building a large-scale and diverse scope of smart machines are coalescing and being tested by "first movers." Once they offer significant  cost reduction and productivity improvement, companies will embrace them by employing smart machines in place of humans.

IT cost is typically about four percent of annual revenue of the companies, whereas the labor costs that can be rationalized by smart machines are as high as 40 percent of revenue in some knowledge and service industries. This gives considerable scope for deploying further IT systems.

The firms that have not begun to develop programs and policies for a "digital workforce" by 2015 will not perform in the top quartile for productivity and operating profit margin improvement in their industry by 2020. As a direct result, the careers of CIOs who do not begin to champion digital workforce initiatives with their peers in the C-suite by 2015 will be cut short by 2023.

http://www.gartner.com/newsroom/id/2605015


Books on Smart Machines


Manufacturing Intelligence for Industrial Engineering: Methods for System Self-Organization, Learning, and Adaptation: Methods for System Self-Organization, Learning, and Adaptation

Zhou, Zude
IGI Global, 31-Mar-2010 - Computers - 407 pages

The manufacturing industry has experienced dramatic change over the years with growing advancements, implementations, and applications in technology.

Manufacturing Intelligence for Industrial Engineering: Methods for System Self-Organization, Learning, and Adaptation focuses on the latest innovations for developing, describing, integrating, sharing, and processing intelligent activities in the process of manufacturing in engineering. Containing research from leading international experts, this publication provides readers with scientific foundations, theories, and key technologies of manufacturing intelligence.
https://books.google.co.in/books?id=aejvZWm2_a8C

Manufacturing in Real Time: Managers, Engineers and an Age of Smart Machines

Gian F. Frontini, Scott Kennedy, Scott L. Kennedy
Butterworth-Heinemann, 2003 - Business & Economics - 206 pages

The development of self-operating machines is the foundation of modern manufacturing. This current manufacturing environment is based on automation and smart machines that have the ability to make things with a level of accuracy and consistency that humans cannot match. In order to maximize efficiency, engineers and managers need to change their outlooks, processes and strategies and as a result, adopt new methods and management systems.

The authors demonstrate what is needed by first presenting a brief history of manufacturing and the changes we have already seen and then make their way into the current manufacturing environment. Topics covered include supply chain management, product streams, the role of automation in the supply chain, the relationships between machines and people in automated product streams (looking at what machines do best and what humans do best), variation and quality control, statistical process control, the flow of information in a supply chain and how all of these elements are effected by new technologies and need to be changed to allow for maximum efficiency as we move more toward automation in factories.

*Discover the impact of new technologies on the future shape on the manufacturing industry
*Excellent examples used throughout to demonstrate each idea and process
*Includes a CD with lectures, slides, tutorials, dynamic models and much more!
https://books.google.co.in/books?id=Cx0YriQ-7owC


Bibliography

http://www.schneider-electric.co.uk/en/download/document/170226-MSol-thought-leadership/

http://www.ni.com/en-in/innovations/transportation-and-heavy-equipment/smart-machine-control.html


High Productivity Through Smart Factories



Updated 17.9.2022,  18.7.2022, 27.5.2022,  25.2.2022, 2 Nov 2021,  11 Oct 2020,  18 Sep 2020
7 July 2019,  16 August 2017, 13 July 2017

4 comments:

  1. Smart Textile Machinery. Digitalized smart textile factory. Machines and Productivity of Processes.
    Productivity Improvement Through Smart Machines.
    #IndustrialEngineering #Productivity #CostReduction
    https://nraoiekc.blogspot.com/2017/07/productivity-improvement-through-smart.html

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