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Modern Industrial Engineering - Industrial Engineering through MES Data

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Popular E-Book on IE,

Introduction to Modern Industrial Engineering. 

In 0.1% on Academia.edu. 10,600+ Downloads so far.

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Related Posts

Industrial Engineering through Digital Twins

Industrial Engineering through Process Mining

Cost Measurement in Manufacturing Execution System (MES)

Waste Measurement and Reporting Using MES - Manufacturing Execution System


Recent Information

19.9.2023

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Search MES Data Analytics

https://www.linkedin.com/advice/0/what-latest-trends-innovations-mes-data-analysis-reporting


Added by me in the above post.


Narayana Rao KVSS

Professor (Retired), NITIE - Now IIM Mumbai - Offering FREE IE ONLINE Course Notes


Process plan needs to be fed in detail into MES to execute each step in the plan. The process has to be performed at each work station as per plan. All the inputs required at the work station are to be made available by persons or machines concerned at the time instant the process has to start. The time stamps at each work station will record the time at which the task at the work station is started and the time at which it is completed. This time for each cycle can be compared with standard time or allowed time. Delays can be found out from it from this data. Delay elimination is an important task for the managers and supervisors as well as production planners and controllers. Improvements by ind.  engineers have to be recorded in plans.



https://www.mastercontrol.com/gxp-lifeline/manufacturing-data-analysis-software-insights/


Advanced Analytics in Batch Production

You can quickly identify batch production issues with outlier detection and alerts. The manufacturing data analysis software completes all the steps necessary to identify anomalies and then provides the analysis information. 

Step execution duration and outlier detection.

Pattern detection in production record exceptions – Lets you figure out if there’s a recipe or combination of parameters that can cause more record exceptions than normal.

Seasonality detection of rejections in production records – Enables you to determine if there’s a certain time of year when you experience more than the usual number of rejections.




https://www.mastercontrol.com/gxp-lifeline/manufacturing-insights-data-analytics/

The three types of analytics in manufacturing.

#3: Prescriptive Manufacturing Insights

At this level of MES analytics, the program makes suggestions based on the plans and execution data. These suggestions help your manufacturing processes become more efficient and effective.  Prescriptive analytics recommend best practice for maximum benefit. You’ll know which combination of employees can give you the highest quality batch with the highest yield and fewest defects. When there are defects,  the system can perform a root cause analysis and tell you what the problem was. A lot of the legwork that humans do now can be done by these advanced programs, which lets the humans in manufacturing focus on more meaningful work. 



https://www.forbes.com/sites/forbestechcouncil/2022/09/29/mes-transformation-part-3-combining-the-power-of-iiot-with-descriptive-analytics/


https://www.mceneryautomation.com/case-study/brewing-mes-standard


https://www.orbis.de/en/sap-orbis-solutions/analytics-mes-dashboard.html


https://www.ge.com/digital/lp/gartner-magic-quadrant-manufacturing-execution-systems-mes


https://www.planettogether.com/blog/data-driven-quality-management-and-process-improvement-in-pharmaceutical-manufacturing


https://www.factbird.com/


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MES for Manufacturing Planning, Scheduling and Dispatching

The MES is a central strategic tool for implementing the requirements of the factory of the future. MES can provide Knowledge and Knowledge Management for Process Chart Based Industrial Engineering.


Industrial Engineering and MES Data

Industrial engineers now have the MES data to access and improve processes. The method of preparing process charts and operation details by direct observation on the shop floor  was developed by Frank Gilbreth and standardized by ASME. Now in the age of digitization, industrial engineer can  get process related information from manufacturing information systems. Manufacturing execution system (MES) is an information system that interacts with lower systems that directly control equipment and directs them to specific tasks as per the orders sent to it by the ERP system. MES also records actual execution of the operation instruction at each equipment and work station. Industrial engineers can examine MES data to understand the process and examine it for improvement. Problems encountered in process and alternatives used by the plant personnel to temporarily overcome the problems are also recorded in the data presenting industrial engineers the opportunity to make required improvements in the process.

MES data provides an approach for process improvement for industrial engineers.

Data Model for Manufacturing Execution System (MES)  - Note


MES Data - MES Brochures and Web Pages

https://www.mpdv.com/en/products-solutions/mes-hydra/processdata/

Keep an eye on process values and detect trends!

Superior products are often manufactured using complex processes which require the utmost precision. Adhering to production parameters like temperature, pressure or flow rates, and evaluating statistics aimed at continuous improvement guarantee high production quality and low scrap rates.

Benefits

Increased process stability through correlation of recorded data with orders, articles, material batches, and more

Reduced scrap due to continuous monitoring of defined process parameters and early detection of trends

Cost savings through multiple use of shared data (e. g. for quality assurance)

Compliance with specifications for complete documentation of the manufacturing process

Support of condition-based maintenance strategies

Process data collection 


Process Data Collection

While the continuous control of production parameters, process values and their recording can now be taken over by sensors, modern machines and plant controls (PLC), the HYDRA module Process Data (PDV) offers functions that go far beyond this. The complete integration of all MES applications on the basis of a central database allows for the correlative examination of other data. The comparison of data to orders, articles, material batches or tools and process values makes a valuable contribution to optimize your production. For example, limit value violations can be detected relating to current orders or manufactured articles. The early detection of trends enables timely intervention and countermeasures. HYDRA PDV transfers process values via a standard interface (e. g. OPC): The collected data can also be used as an input parameter for production-related quality inspections.

Many business units across the enterprise can benefit from an MES system. Our ROI Analyzer reveals the untapped potentials that are still hidden within your production processes.  

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COLLECT, ANALYZE AND OPTIMIZE

Once your processes are in place and your MES system is at work, you can maximize efficiency, yield and quality by collecting and analyzing process data. EZ-MES will allow you to have a seamless integration of your Process Data acquisition, as well as live reports like Product Tracking, WIP and Inventory. This will enable you to make well informed decisions that will improve your bottom line. 


USE EZ-MES TO COLLECT DATA

The real time browser based Manufacturing Execution System EZ-MES collects process data as parts travel through different manufacturing steps. Critical travel data such as start time, end time, resources used, yield, drop outs are automatically logged at a very granular level. 

Data generated by your manufacturing process can be collected via manual input or in an automated way.

In case of manual data collection, EZ-MES has build-in a number of pre-formated and configurable User Interface elements. Forms using such user interface elements allow seamless input of data by humans while supporting that the date is entered correctly. This is be done by using pre-configured radio buttons, dropdown boxes and input fields with validation checks defined via regular expressions.

Many tools in today's manufacturing environment support data collection, such as barcode-readers, forms, equipment, electronic handheld devices and others. Data generated by those and by equipment using sensors, can be automatically feed to EZ-MES by using its open Application Programming Interface (API). This open API allows software tools for automated measurements to access the data and core functions in EZ-MES. 


ANALYZE COLLECTED DATA

EZ-MES contains a number of pre-formatted reports. For the purpose of data analysis, EZ-MES contains 'out of the box' Statistical Process Control (SPC) Reports. SPC is an industry-standard method for measuring and analyzing data for quality during the manufacturing process. Product, Part and Process measurements are gathered by EZ-MES during manufacturing. This data is then plotted on a graph with pre-determined control limits. 

Results that falls within the control limits indicates that everything is operating as expected. Any variation within the control limits is considered to be acceptable due to natural variation in the manufacturing processes. If data consistently falls outside of the control limits, then this indicates that something within the process is likely not running as it is supposed to do. Repairs need to fix the issue before serious defects and possible escalations occur.

OPTIMIZE YOUR PROCESSES

The immediate and real time use of production data collection and analyses is to detect acute production problems or even faults leading to expensive recalls, if not detected in time.  Next to this short term need, there is an obvious and on-going mid- and long term need to further improve both processes and products and reduce costs.

As manufacturing processes are soft configured in EZ-MES instead of being hard-coded, rapid prototyping changes in EZ-MES is relative fast and easy to do, as no programming skills are needed. EZ-MES has an optional Sandbox version which allows you to first try out and simulate changes in your manufacturing processes and in your vertical and horizontal integration of flows. You can dry-run these changes and if accepted, make them available to the Live version of your EZ-MES application. As EZ-MES is a realtime browser application, your changes are immediately deployed to all users, without any need for local software updates.

After the deployment of the changes, you can start collecting and analyzing production data. To evaluate the real world impact of the changes you made. 

https://eazyworks.com/solutions-collect-analyze-and-optimize

Process Data Management, part of ABB Ability™ Manufacturing Execution System for pulp and paper

Configuring your data sources

Your goal: valuable process data seamlessly retrieved from fragmented control systems, interfaced with other data sources, ready to communicate towards the Cloud and the shop floor in real time. 


Our solution: Process Data Management, part of ABB Ability™ Manufacturing Execution System for pulp and paper


ABB has the right combination of domain-specific expertise and knowledge of both IT and OT infrastructure to ensure that your data management approach is closely aligned to your business strategy.


We know how to properly label, model and structure data specific to the pulp and paper operations, how to store, compute and stream high volumes of data securely and cost effectively.


Transforming the pulp and paper industry through systematic data management
27 Apr 2021
John Schroeder 

Good Presentation - MES, Operational Excellence, Data Analytics and Manufacturing Intelligence

https://www.slideshare.net/BoraSusmaz/mes-operational-excellence-data-analytics-and-manufacturing-intelligence


Sanofi: Designing a Data Management Strategy for the Future

May 12, 2021 | Patrick Nadolny

https://www.veeva.com/blog/sanofi-designing-a-data-management-strategy-for-the-future/

https://pdfslide.net/healthcare/sanofi-aventis-analytics-journey-transforming-big-pharma.html


Selecting Cutting Data Tests for Cutting Data Modeling Using the Colding Tool Life Model

Procedia CIRP, Volume 72, 2018, Pages 197-201

https://www.sciencedirect.com/science/article/pii/S2212827118301355


Applying data of historical defects to increase efficiency of rework in assembly

Procedia CIRP, Volume 72, 2018, Pages 255-260


Big data analytics for operations management in engineer-to-order manufacturing
Procedia CIRP, Volume 72, 2018, Pages 209-214

Pin Point MES


THE MES SOLUTION that helps you reach your productivity and quality goals.

https://www.pinpointinfo.com/blog/manufacturing-process-improvements-data-analytics


https://www.pinpointinfo.com/blog/mes-productivity-case-study

https://www.pinpointinfo.com/blog/lean-and-mes-minimize-waste-improve-productivity

Boost Error-Proofing in Manufacturing with an MES Solution
Jarda Smrz, President, Pinpoint
April 30, 2020
https://www.pinpointinfo.com/blog/boost-error-proofing-in-manufacturing-mes-solution

https://www.pinpointinfo.com/blog/operator-driven-production-data-manufacturing-success

https://www.pinpointinfo.com/blog/uncovering-the-hidden-factory

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MES Softwares - Interesting Information

SAP ME by SAP


https://en.t-h.de/case-studies/overview.html


Automotive: Transparent Production with real-time Monitoring

With SAP Manufacturing Integration and Intelligence (SAP MII) in connection with Best Practice solutions, supplied by Trebing + Himstedt and integrated into the application, the components supplier WITTE Automotive seamlessly connects its shop floor systems with SAP ERP. This enables the company to monitor manufacturing processes in real time and to maintain a transparent, comprehensive view of its key data at any time. Both are vital leverages to optimize production processes and render them more cost-efficient.

https://en.t-h.de/case-studies/plant-performance-management.html


Honeywell Connected Plant

by Honeywell


https://www.honeywellprocess.com/en-US/online_campaigns/connected_plant/Pages/home.html


https://www.youtube.com/watch?v=QUjisqHmok4

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Oracle Manufacturing Cloud

by Oracle


https://www.oracle.com/in/scm/manufacturing/


https://docs.oracle.com/en/cloud/saas/supply-chain-management/20b/faumf/production-process-design.html


https://www.wipro.com/en-IN/applications/real-time-mes-putting-precision-into-your-plant/

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Siemens Opcenter

by Siemens

https://www.industrialautomationindia.in/articleitm/8474/Scanfil-selects-Siemens-Opcenter-to-digitalize-operations/articles

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TrakSYS

by Parsec

https://fdocuments.in/document/traksys-customer-case-study-aps-group.html

https://fdocuments.in/document/traksys-customer-case-study-aps-group.html

https://www.youtube.com/watch?v=BO0HgEOxQiQ


Information Technology for Manufacturing: Reducing Costs and Expanding ...

By Kevin Ake, John Clemons, Mark Cubine, Bruce Lilly

https://books.google.co.in/books?id=NZdw2971DSEC


MES Modules - MPDV


Shop Floor Data

Machine Data

Shop Floor Scheduling

Dynamic Manufacturing Control

Tool & Resource Management

Material & Production Logistics

Tracking & Tracing

Energy Management

DNC & Configuration Data

Process Data

In-Production Inspection

Incoming Goods Inspection

Complaint Management

Test Equipment Management

FMEA

Premium & Incentive Wages

Personnel Scheduling

Time & Attendance

Personnel Time Management

Access Control


https://www.mpdv.com/en/products-solutions/mes-hydra/shop-floor-data/


Gartner's Magic Quadrant for MES


2021 - https://mes.criticalmanufacturing.com/2021-gartner-magic-quadrant/

Videos on MES

Critical Manufacturing


__________________


https://www.youtube.com/watch?v=PLntjUFMLk8&t=3s

https://www.youtube.com/watch?v=5zoUit97Rx4&list=UULh-scVR4DHPfY1GrnufQnw

__________________

More Videos

RSA Solutions

https://www.youtube.com/watch?v=5FWWoCz90Y8

https://www.youtube.com/watch?v=Rz02m0NiKZ0


Corso Systems

https://www.youtube.com/watch?v=g2Zx3gYiSuM


Mahindra Presents MES for Automotive Operations

•20 Oct 2015

MES implemented at Chakan MVML

Rockwell Automation

29.8K subscribers

Mahindra provides a detailed system tour of their Rockwell Software ProductionCentre MES for automotive manufacturing operations and enterprise systems.

https://www.youtube.com/watch?v=o8j2udvlMyU


Brock Solutions

https://www.youtube.com/watch?v=m38GaSbzDqs






MES and Seven Waste Model

An interesting explanation of seven wastes by Deloitte Insights


Image source: https://www2.deloitte.com/xe/en/insights/focus/industry-4-0/digital-lean-manufacturing.html  - Good content on the concept of digital lean


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MES Software Helps Plants Integrate Cross-Functional Platforms

Islands of automation are giving way to plant-wide (even enterprise-wide) efforts that yield performance analysis and front-office profit maximization.

11 April 2008


Evolving Price/Performance of DCS - PLCs


“In the mid-1980s,  Serial No. 1 of the Rosemount [now Emerson Process Management] RS3 [DCS],  gave 40-megabytes of hard drive to work with and  cost was $2 million. 

Today, a single programmable logic controller (PLC) can perform the same function  and the cost of even a high-end PLC is about $500. More impressive: PLCs  today handle motion, motor and process loop controls that a decade ago required multiple vendors, tools, parts and training that far exceeded the hardware cost.

Automation systems is standardization

A key enabler of today’s automation systems is standardization.  ISA-88 and ISA-95 consist of common terms and definitions for manufacturing functions; common process models that map real-world plant processes and data flows; and programming conventions shared by automation professionals. As such, they serve both as templates for training as well as technology development. Some of their key features:

ISA-88 and allied efforts (such as Make2Pack for packaging) address most production environments found in food plants, including automated product changeovers. This standard first affected first-tier control software such as human-machine interface (HMI) and supervisory control and data acquisition (SCADA) software and grew with batch and manufacturing execution systems (MESs).

ISA-95 is a control-to-enterprise standard built upon ISA-88. It  maps workflows between production, packaging, quality and maintenance. It broadens the effectiveness of MES-level models with extensions from production to functions throughout operations and up to the ERP level. 

Many companies are finding significant savings in more rapid integration of their SAP systems with factory processes via the  standard interface provided by  ISA-95. 

Smithfield refined its  systems using  Rockwell’s software conformance to such standards in a greenfield plant. The strategy now is being implemented gradually across all plants. It integrates plant applications with the ERP system and the web services make this information available to remote managers monitoring plant-by-plant performance levels. Sales personnel can track orders to levels of partial completion.

Executing a command performance

Most companies with revenues above $250 million are using MES systems at some level. 

MES can be seen as having has two tiers of benefits: production management and performance management. Standard features typically include data collection and event-driven alerts for operator intervention such as clean-in-place (CIP), hazards analysis and critical control points (HACCP) programs or material replenishment.

Systems rise to the level of performance management when they include modules for or integrate with functions outside production and incorporate deeper analytical functions such as optimal equipment effectiveness (OEE).

The practice of OEE is accompanied by aggregated data presented as key performance indicators (KPIs), such as a single-value index or percentage of a production line’s performance against an ideal goal. It’s one of many uses for KPIs that can be presented in dashboard-style values, dials or graphic bars.

Each KPI, wherever it is displayed, should be role-specific to the operator, supervisor or manager using it. According to Walt Staehle, an ex-Kraft Foods manufacturing executive who installed MES, laboratory and other systems across 50-plus Kraft plants during this 20-plus years there,  Kraft recouped $1.6 million by reducing variability in raw materials-to-finished goods conversion and improving asset utilization by using a simplified (uptimeonly) version of OEE as part of a collaborative, real-time performance management strategy. 

Key performance indicators are measured and used to run  businesses and shop floors in many companes.

The economic justification for plant automation is the same, whether a plant uses PLCs or a DCS and whether the plant is dedicated to candy bars or corn wet milling.

https://www.foodprocessing.com/articles/2008/083/

OEE Metrics Reveal Return on Investment

Plant operators are proving the financial value of their automation investments with measurable data on overall equipment effectiveness (OEE) and other hard metrics.

Rob Spiegel, Apr 1st, 2005

https://www.automationworld.com/products/software/article/13303509/oee-metrics-reveal-return-on-investment


Six Sigma Takes Root in Rich MES Data

by Charles Rastle and Julie Fraser

Quality Digest Magazine, July 2004

Author: Charles Rastle is an industry strategic marketing manager for Rockwell Automation’s Global Manufacturing Solutions group.

https://www.qualitydigest.com/june04/articles/04_article.shtml   (23 November 2020)


Updated on 20.9.2024,  19.9.2023, 29.12.2021,  19.9.2021, 8.8.2021, 29.4.2021 1 Feb 2021, 8 December 2020

First published on 22 November 2020





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Modern Industrial Engineering - Industrial Engineering through Digital Twins

Popular E-Book on IE

Introduction to Modern Industrial Engineering.  

In 0.5% on Academia.edu. 10,550+ Downloads so far.

FREE Download from:

https://academia.edu/103626052/INTRODUCTION_TO_MODERN_INDUSTRIAL_ENGINEERING_Version_3_0 

--------------------


Lesson 117 of  Industrial Engineering ONLINE Course


Part of Computer Aided Industrial Engineering (CAIE) - Proposal by Prof. Narayana Rao K.V.S.S.

https://nraoiekc.blogspot.com/2021/09/computer-aided-industrial-engineering.html


Industrial engineers can use digital twins to observe operations in processes. The work station in action will be available on their table to observe in real time as well as offline number of times and even in slow motion to understand the process and come with alternatives. Industrial engineers need not use video filming of the process anymore.

As alternatives are generated by industrial engineers to improve the process, they can use digital twin to simulate the new operation. They need not any more ask for time to experiment with the modified operation on a physical work station.  They have the cyber version of the work station at their disposal to modify the operation and observe the performance for effectiveness and efficiency.

Digital twin technology provides real-time, interactive simulations of  equipment and process at  manufacturing plants. Digital twins  can help manufacturers improve innovation, efficiencies, quality, and yield.

Digital twin technologies can intelligently simulate product,  equipment and process  during the development lifecycle of the product and process. 

What is  a Digital Twin?  

A digital twin is a virtual representation of a physical entity or system.   It is a dynamic, simulated view of a physical product that is continuously updated throughout the design, build and operation lifecycle. The digital twin  evolves as the physical product progresses and matures.

The digital twin is  informed by sensors embedded in twin’s physical counterpart. The data is  fed into an IoT platform and enriched by artificial intelligence. The virtual replication of the object is presented on high-definition, immersive displays that engineers and operators can use to visualize the object’s status and interact with it in real time without disrupting production.

Teams can use a digital twin to modify product designs; and examine them through  what-if simulations without building physical prototypes.  Similarly the manufacturing processes can be modified in digital twin and can be assessed for benefits. Different views of a digital twin can be created for different  individual departments. Hence a digital twin can be created for industrial engineering departments.

The digital twins and their use in simulation based on modifications in product and process designs  are made possible by cognitive manufacturing or artificial intelligent manufacturing, which leverages cognitive computing, the Industrial Internet of Things (IIoT), data science and advanced analytics to help organizations improve  manufacturing processes. 


Digital Modeling and Digital Thread: Key Enablers for Digital Twin Solutions

Data-enriched simulations—can be used to model and remodel the performance of plant equipment under a variety of what-if scenarios. The technique can help identify the best approaches for improving key performance indicators (KPIs) for the manufacturing process and product quality.

Asset maintenance is also improve through digital twin based data-driven modeling. Machine learning, deep learning and artificial intelligence can be applied to dynamic process monitoring and machine health data to better detect anomalies and predict failures. The approaches can transform maintenance into a proactive activity and even enable feedback loops that automate procedures to resolve maintenance issues.


Digital Thread

The digital thread is the traceable flow of data that interconnects all relevant systems and functional processes involved in a product’s lifecycle and informs the digital twin and digital modeling activities. 

The digital thread  facilitates the exchange of real-time data between sensors that are monitoring a physical object and the object’s digital twin. The digital thread yields an end-to-end perspective of issues and problems that might emerge during the manufacturing life cycle. 

PLM becomes more responsive and agile, enabling a company to produce high-quality products while increasing manufacturing efficiencies. The digital thread uses ISA-95 standards to automate communications between control and enterprise systems. The standards facilitates integration with companies that are partners in the digital twin ecosystem.

Digital twin technologies inform and guide continuous engineering practices. The tools help industrial engineers, other engineers and operators  create and refine products at all stages of the product’s lifecycle: design, build, and operate. Industrial systems engineers design and build products, processes and processing facilities. Industrial engineers improve products and processes during operations.

Manufacturers are always striving to optimize quality, efficiency and yield through industrial engineering. Industrial engineers can now use digital twin technologies to understand how potential changes in the manufacturing process might impact production outcomes and modify the manufacturing process elements  accordingly to achieve targeted improvements. 

 “Operate” refers to operation, servicing and maintenance activities. Companies can apply digital twin solutions in these contexts to increase uptime and improve operating efficiencies while making sure equipment and products function at optimum levels. 

Digital twin solutions introduce unprecedented conveniences in this use case because the technology enables technicians to “see” inside the virtual representation of a device to identify potential problems. The digital twin can also incorporate information from enterprise asset management (EAM) software and automation programs so technicians have up-to-the-minute information about a machine’s operating status, recent alarms or maintenance activities. The solution can also advise technicians on how to perform maintenance procedures for the problems they’re addressing. 

Manufacturers can enable these capabilities 



An Integrated Framework for Digital Twin Implementations


Enterprise applications: The framework makes it possible to use real-time data from enterprise applications to support decision-making on the shop floor and in corporate sales, strategy and operations offices. 

Typical applications include predictive maintenance tools, enterprise resource planning (ERP) and enterprise asset management (EAM) programs, supply chain management software, manufacturing execution systems (MES), and customer relationship management (CRM) solutions.



Implementing digital twin:

• Obtain the CAD/CAM versions of the machine or product from the team or engineering partner that produced the original design.

• Create a new digital model of the machine that considers the equipment’s mechanics, the machine’s interactions with other equipment in the facility, the product being produced, and relevant operational or enterprise software applications.

• The physical machine has to be monitored by sensors and connected to a gateway that integrates with an IoT platform. 

• Give special attention to data quality at every stage of design, build and operate.


Apply cognitive analytics and machine learning to the sensor data  to bring real-time context and characteristics to the digital twin.

• Implement a digital thread capability to facilitate information flow between data 

sources and applications.

• The solution has to  generate analytics at every stage of the lifecycle so that  improvements at each stage of a project and overall can be made

• Provide displays that enable teams to view and interact with the digital model on the shop floor or from their corporate offices. 

• Use an open approach that avoids centralizing data in a proprietary system so your digital twin solution can be used by all stakeholders. 

• Conduct a proof of concept project, using one machine or one operation. Once that is in place and working, expand it to an entire manufacturing line.


Digital Twin Technologies help companies transform their operations through business and operating models that are enabled by the IoT and led by analytics to optimize efficiency, customer-centric strategies, economic growth and maximum asset productivity.


New 2024

Foundational Research Gaps and Future Directions for Digital Twins

NAP 2024

https://nap.nationalacademies.org/download/26894


2022

Analyzing the Implementation of a Digital Twin Manufacturing 

by JH Loaiza · 2022 ·

https://www.mdpi.com/2079-8954/10/2/22/pdf  


Digital Twins - Google Books



Hands-On Azure Digital Twins: A practical guide to building distributed IoT solutions

Alexander Meijers

Packt Publishing Ltd, 03-Mar-2022 - Computers - 446 pages


In today's world, clients are using more and more IoT sensors to monitor their business processes and assets. Think about collecting information such as pressure in an engine, the temperature, or a light switch being turned on or off in a room. The data collected can be used to create smart solutions for predicting future trends, creating simulations, and drawing insights using visualizations. This makes it beneficial for organizations to make digital twins, which are digital replicas of the real environment, to support these smart solutions.

This book will help you understand the concept of digital twins and how it can be implemented using an Azure service called Azure Digital Twins. Starting with the requirements and installation of the Azure Digital Twins service, the book will explain the definition language used for modeling digital twins. From there, you'll go through each step of building digital twins using Azure Digital Twins and learn about the different SDKs and APIs and how to use them with several Azure services. Finally, you'll learn how digital twins can be used in practice with the help of several real-world scenarios.

By the end of this book, you'll be confident in building and designing digital twins and integrating them with various Azure services.

https://books.google.co.in/books?id=QGpEEAAAQBAJ


DigiTwin: An Approach for Production Process Optimization in a Built Environment

Josip Stjepandić, Markus Sommer, Berend Denkena

Springer Nature, 23-Aug-2021 - Technology & Engineering - 259 pages

The focus of this book is an application of Digital Twin as a concept and an approach, based on the most accurate view on a physical production system and its digital representation of complex engineering products and systems. It describes a methodology to create and use Digital Twin in a built environment for the improvement and optimization of factory processes such as factory planning, investment planning, bottleneck analysis, and in-house material transport. The book provides a practical response based on achievements of engineering informatics in solving challenges related to the optimization of factory layout and corresponding processes.

This book introduces the topic, providing a foundation of knowledge on process planning, before discussing the acquisition of objects in a factory and the methods for object recognition. It presents process simulation techniques, explores challenges in process planning, and concludes by looking at future areas of progression. By providing a holistic, trans-disciplinary perspective, this book will showcase Digital Twin technology as state-of-the-art both in research and practice.


Twin-Control: A Digital Twin Approach to Improve Machine Tools Lifecycle

Mikel Armendia, Mani Ghassempouri, Erdem Ozturk, Flavien Peysson

Springer, 05-Jan-2019 - Technology & Engineering - 296 pages

This open access book summarizes the results of the European research project “Twin-model based virtual manufacturing for machine tool-process simulation and control” (Twin-Control). The first part reviews the applications of ICTs in machine tools and manufacturing, from a scientific and industrial point of view, and introduces the Twin-Control approach, while Part 2 discusses the development of a digital twin of machine tools. The third part addresses the monitoring and data management infrastructure of machines and manufacturing processes and numerous applications of energy monitoring. Part 4 then highlights various features developed in the project by combining the developments covered in Parts 3 and 4 to control the manufacturing processes applying the so-called CPSs. Lastly, Part 5 presents a complete validation of Twin-Control features in two key industrial sectors: aerospace and automotive. The book offers a representative overview of the latest trends in the manufacturing industry, with a focus on machine tools.

Digital Twin Driven Smart Manufacturing

Fei Tao, Meng Zhang, A.Y.C. Nee

Academic Press, 07-Feb-2019 - Technology & Engineering - 282 pages

Digital Twin Driven Smart Manufacturing examines the background, latest research, and application models for digital twin technology, and shows how it can be central to a smart manufacturing process. The interest in digital twin in manufacturing is driven by a need for excellent product reliability, and an overall trend towards intelligent, and connected manufacturing systems. This book provides an ideal entry point to this subject for readers in industry and academia, as it answers the questions: (a) What is a digital twin? (b) How to construct a digital twin? (c) How to use a digital twin to improve manufacturing efficiency? (d) What are the essential activities in the implementation of a digital twin? (e) What are the most important obstacles to overcome for the successful deployment of a digital twin? (f) What are the relations between digital twin and New Technologies? (g) How to combine digital twin with the New Technologies to achieve high efficiency and smartness in manufacturing?

This book focuses on these problems as it aims to help readers make the best use of digital twin technology towards smart manufacturing.

Analyzes the differences, synergies and possibilities for integration between digital twin technology and other technologies, such as big data, service and Internet of Things

Discuss new requirements for a traditional three-dimension digital twin and proposes a methodology for a five-dimension version

Investigates new models for optimized manufacturing, prognostics and health management, and cyber-physical fusion based on the digital twin

Table 1.1 Theoretical concept of Digital Twin

https://books.google.co.in/books?id=PvKGDwAAQBAJ

Video:  Continuous Engineering with Digital Twin

22 Jan 2018

Software Education

IBM has great support for the Digital Twin.  Have a look at the Continuous Engineering story.

_____________


_____________

Example of car reversing is interesting. Digital twin can capture every reversing event and in the case of any mishap, the cause can be analyzed using the digital twin information.


Video: Introduction to Digital Twin: Simple, but detailed - IBM

28 Jun 2017, IBM Internet of Things

What is the Digital Twin?  

Digital twin is the ability to make a virtual representation of the physical elements and the dynamics of how an Internet of Things device operates and works. It's more than a blueprint, it's more than a schematic. It's not just a picture. It's a lot more than a pair of  ‘virtual reality’ glasses. It's a virtual representation of both the elements and the dynamics of how an Internet of Things device responds throughout its lifecycle. It can be a jet engine, a building, process on factory floor, and much, much more.  

https://www.youtube.com/watch?v=RaOejcczPas

See the presentation on Slideshare  https://www.slideshare.net/IBMIoT/ibm-watson-internet-of-things-introducing-digital-twin

See the full session https://www.youtube.com/watch?v=gUCCnVXgYvw


Machine Tool Industrial Engineering Using Digital Twins

Machine Tool Digital Twin with Life Cycle features

Summary

A new approach to simulate machining processes has been developed based in SAMCEF Mecano FEM solver. A digital representation of machine tools can be developed in this environment by combining structural FEM analysis, specific elements for the feed drives and control loop models. The novelty of this approach consists in the integration of new machining process models that provides the chance to evaluate machine tool performance during manufacturing operations.


Standards for digital manufacturing webinar: recordings and presentations are now available!

On 20 October 2020, EFFRA, in association with the ConnectedFactories CSA, organised "the standards for digital manufacturing" webinar. The Webinar focused on use cases and best practices that illustrate how standards are used in research & innovation in digital manufacturing. Special attention has been dedicated to the added value as well as gaps and needs. 
https://www.effra.eu/news/standards-digital-manufacturing-webinar-recordings-and-presentations-are-now-available

VERICUT Machine Tool Digital Twin



CNC Digital Twins Help Simulate Success
Identify variances before production begins on the floor.
IEN Staff
Aug 23, 2022

VERICUT digital twin ready for lift-off

For most, CAM covers every step of the manufacturing process, including the engineering master model of the component, stage definitions associated to each operation, fixturing and tooling, cutting tools, the NC toolpath and set-up information. The ‘digital twins’ of each element allow the engineering teams within the companies to test and prove processes in a virtual environment before they are applied – error free – to the real world. With OTIF (On Time In Full) being a key performance indicator for many, it is not unusual for 90 per cent or more of the machine tools used to be fully simulated.

https://www.cgtech.com/component/k2/item/377-vericut-digital-twin-ready-for-lift-off.html

March 2018

The ESPRIT CAM system from DP Technology - Digital Twin Machining Simulation for Greater Productivity in the Smart Factory

ESPRIT allows users to create a digital twin of their machine tools for programming, optimization and simulation. This virtual machine ensures that whatever happens on screen will also occur on the shop floor. Workpieces and cutting tools are set up virtually, resulting in exacting simulations, greater productivity and better toolpaths for higher quality parts. A digital thread ties together each step of the workflow from CAD design to finished part.

https://www.espritcam.com/

Digital Twins for Cutting Tools

2017-07-17

Digital Twins for Cutting Tools

Digitalisation of tool- selection and assembly creation 

The digitalisation of  tooling item selection and tool assembly creation can help to significantly increase efficiency and machining security. Cutting tool data can  be gathered more accurately and used to create precise digital twin representations.

Creating tool assemblies is  a somewhat laborious task for the CAM programmer, where there exist several opportunities for error including  failing to select the optimum tool items. Many typical tool assemblies can take up to 1 hour to create. 

Creating a digital twin representation for a tool assembly simulation is still difficult. In order to make the most accurate possible representation of a tool assembly in a CAM system, the creator would first need to search various vendors’ catalogues, download the 3D model files, and assemble them in a CAD programme. 

Digital database of tools can help in tool selection. An integrated tool database  would allow CAM programmers to select from holders, tools and inserts for milling. Once data such as component, type of machining operation and material has been input, users can get tool recommendations and suggested cutting parameters.  

CoroPlus® ToolGuide from Sandvik Coromant is a digital cutting tool database. It uses an open Application Programming Interface (API) to connect with the CAM software.  CoroPlus ToolGuide enables users to find a suitable cutting tool for a given task. It provides  an organised list of all the suitable tools, with the most economical choice at the top. It will further show the suggested machining process and cutting data.

The list is generated by an algorithm that matches the stated task and conditions with Sandvik Coromant tools. This algorithm combines information about the different machining processes that can be used for different tasks with the product data on the tool that has  information on the machining processes to which the cutter is suited. The data of the selected tools can be sent to CoroPlus® ToolLibrary, where standard tool assemblies can be created ready for export to the CAM or simulation software.

Until recently there has been no industry standard for communicating tool data to tool libraries.  CAM vendors, machine tool builders and tool suppliers have historically had their own way to denominate and structure tool information so far. Now ISO 13399 has been created so that tool information is available in a standard format from all vendors. Sandvik Coromant, the KTH Royal Institute of Technology and other players in the metal cutting sector are behind the development of ISO 13399, which is now a globally recognised way of describing tool data.

This international standard defines tool attributes – for example length, width and radius – in a standardised way. ISO 13399  simplifies the exchange of data for cutting tools. When all tools in the industry share the same parameters and definitions, communicating tool information between software systems becomes very easy.

CoroPlus ToolLibrary is built on the ISO 13399 structure and is open to all tooling suppliers, ensuring there is no longer any need to interpret data from paper catalogues and then manually enter it into the system.

CoroPlus ToolLibrary allows CAM programmers to work with any tool vendor catalogue compliant to ISO 13399 standards and to create assemblies safe in the knowledge that all suggested items will fit together. The results can be viewed instantly in 2D and 3D, while users can also digitally store all information about the tools. Once saved, programmers simply import the tool assembly into their CAM or simulation software. All of the tool data is pre-set and a 3D model included.

Users report that this efficient and easy process makes it possible to cut the time from tool assembly to simulation by at least 50%. There is a much better chance of making the right tool choice by using digital databases of tools. Having accurate tool data, real tool shape and a precise digital twin representation will help to detect and avoid collisions  during simulation routines.

Through the latest digital solutions such as CoroPlus ToolGuide and CoroPlus ToolLibrary, it is possible to demonstrate how much easier and faster pre-machining tasks can be executed. Both are part of the wider CoroPlus® suite of connected solutions from Sandvik Coromant aimed at helping manufacturers prepare for Industry 4.0.

https://www.sandvik.coromant.com/en-gb/news/pages/how-to-create-the-perfect-digital-twin.aspx



Integration of digital twin and deep learning in cyber-physical systems: towards smart manufacturing

Jay Lee,Moslem Azamfar,Jaskaran Singh,Shahin Siahpour

Volume2, Issue1, March 2020, Pages 34-36


Cyber-physical system (CPS) and digital twin (DT) are two essential elements  of smart manufacturing systems.  CPS enhances communication between smart manufacturing entities (sensors, actuators, control, etc.) and cyber computational resources to facilitate monitoring, data collection, perception, analysis, and real-time control of manufacturing resources. DT integrates historical and real-time data obtained from physical systems with physics-based models and advanced analytics to create digital counterparts with high integrity, awareness, and adaptability to provide predictive services to manufacturing entities. It enhances transparency and feasibility of functions in CPS and facilitates real-time monitoring, simulation, optimisation, and control of cyber-physical elements. A DT-based CPS (DT-CPS) constantly acquires, integrates, analyses, simulates, and synchronises data across multiple stages of the product life cycle to provide on-demand predictive services to different users in both physical and cyber spaces. 

Deep learning (DL) is part of a broader family of machine learning (ML) methods that have the capability to use raw data and automatically provide the representations required for various applications such as classification, regression, clustering, and pattern recognition. DL is very powerful in discovering complex structures in high-dimensional data and therefore, it has enormous applications in the manufacturing domain. It allows higher levels of abstraction without manual feature engineering and its high performance has been validated in other domains such as speech recognition, image processing, inventory management, and fault detection and diagnosis.

https://ietresearch.onlinelibrary.wiley.com/doi/10.1049/iet-cim.2020.0009



4/1/2019 

DIGITAL TWIN-DRIVEN MANUFACTURING

Machining Demonstration Shows the Digital-Twin Concept in Action

A demonstration at IMTS 2018 showed that all of the pieces are now in place, making  digital-twin manufacturing feasible for shops. 

Mark Albert, Editor Emeritus, Modern Machine Shop

https://www.mmsonline.com/articles/machining-demonstration-shows-the-digital-twin-concept-in-action



Digital Twins in Chemical Plants for Productivity and Quality

Bibliography





























Digitalisation and IoT have been identified by the UK’s Chemistry Council as two of the key strategy levers to accelerate innovation-led growth in the chemical industry.

-------------------------





Updated on 26.8.2024, 20.9.2022,  26.11.2021,  20.9.2021,  8 January 2021, 15 December 2020

First published on 15.11.2020









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Wednesday, September 18, 2024

Supply Chain Industrial Engineering - Concept and Bibliography

 

Introduction to Modern Industrial Engineering.  

by Prof. Narayana Rao K.V.S.S.

In 0.5% on Academia.edu. 10,525+ Downloads so far.

FREE Download from:

https://academia.edu/103626052/INTRODUCTION_TO_MODERN_INDUSTRIAL_ENGINEERING_Version_3_0 




Every engineering area has associated industrial engineering.
Every Engineering Topic has Industrial Engineering and Productivity Aspects.
Engineering Topics and Industrial Engineering and Productivity Aspects.


What is Industrial and Systems Engineering?

IISE Definition of Industrial Engineering

Industrial and systems engineering (ISE) is concerned with the design, improvement and installation of integrated systems of people, materials, information, equipment and energy. It draws upon specialized knowledge and skill in the mathematical, physical, and social sciences together with the principles and methods of engineering analysis and design, to specify, predict, and evaluate the results to be obtained from such systems.

https://nraoiekc.blogspot.com/2022/03/industrial-engineering-iise-definition.html

Note: 

Industrial and systems engineering (ISE) is concerned with the design, improvement and installation of integrated systems ...   to specify, predict, and evaluate the results to be obtained from such systems.

It is result orientation. Primarily productivity orientation.

Simple Explanation by Narayana Rao K.V.S.S.

Industrial engineering is system efficiency engineering. Its main components are productivity science, productivity engineering and productivity management.

Supply chain is a system. There is supply chain IE.


Similarly every management area has associated industrial engineering.
Supply chain management area has supply chain industrial engineering function to be fulfilled by supply chain managers in association with industrial engineers.


Supply Chain Industrial Engineering - Concept

SCM


Supply chain (SC) extends from suppliers to the ultimate customer. Supply chain fulfills the order given by the customer. So we can visualize marketing activity and sales activity that gets the customer order. Once the order is received by the organization, supply chain management (SCM) activity takes over and fulfills the order, that is delivers the product or the service and collects the payment. If a return is there, SCM has to take care of that also. 

In practice, the supply chain, that is focus of a company starts from the level of suppliers the company would like to include. Some company may include tier 2 suppliers, suppliers supplying to immediate suppliers or tier 1 suppliers. The ultimate customer who buys for personal use is included in the supply chain by definition.

What are the tasks of supply chain management. Production, inspection, transport, storage, after sales service, maintenance of equipment and facilities, production planning and control, production design, process design etc. fall under supply chain management. In a way, supply chain management is extension of works management, the earlier concept that used to include supply side management also. 


SCIE


Industrial engineering is an engineering based discipline to take care of efficiency of systems. When efficiency increases, increased production of specified effectiveness or quality or customer satisfaction takes place. Hence when system efficiency increases, total effectiveness of the system goes up. Supply chain management offers scope to industrial engineers to go to supplier plants and offer IE expertise and support in the supplier development task. The two important performance dimensions of supply chain are responsiveness and efficiency. Industrial engineers focus on efficiency. As supply chain designers change engineering configurations to increase responsiveness, industrial engineers follow them to incrementally modify the configuration to increase efficiency while maintaining responsiveness for each unit supplied.

The follow three activities are relevant to include in this context.

Product Design, Process Design & Reengineering

Process design is the original design. Supply chain has original design to provide required responsiveness and attainable efficiency. Reengineering is the fundamental rethinking and radical redesign of processes to improve performance dramatically in terms of cost, quality, service, and speed based on developments in science, technology or process management. Process reengineering is about engineering redesign and is done undertaken as a major project. It would normally involve substantial capital investment as number of new facilities including machines and equipment are acquired. It is normally undertaken by the facilities engineering and process engineering (process planning) department.

Product designs are also modified by industrial engineers to reduce cost and increase productivity.

Process Analysis
Process analysis leads to process improvement. To analyze the process, documentation of the process needs to be done of the working of the existing process as taking place in the shop now. This activity of recording and analyzing existing processes is the main task undertaken by industrial engineers. It is incremental improvement of the process at planned periods to capture new developments in engineering and creative ideas to apply the existing knowledge to processes inside the company. In this exercise effort is made to involve many in the company by circulating existing process charts.  Examining  the strategic issues also can help identify opportunities for improvement apart from operational issues. A gap analysis can be done between a process’s competitive priorities and its current competitive capability requirements.

In engineering and manufacturing process, industrial engineers carry out process improvement to improve productivity. Process improvement is based on the systematic study of the activities and flows of each process to improve it. Productivity science, engineering and management activities are involved in process productivity improvement. Supply chain industrial engineering is process study and analysis in the area of supply chain management.

Process Improvement Based on Operator/Supervisor/Engineer Suggestions and Shop-floor Based Improvements

Process improvement is based on the   understanding of  the process, and digging out the details. Hence frontline operators have significant ideas to contribute to process improvement. Through seeking their suggestions, process improvement is made a continuous process and incremental improvements at small and micro level keep taking place. In Toyota Motors, Ohno gave responsibility to shop floor personnel also for process improvement apart from process planning and industrial engineering.
https://nraomtr.blogspot.com/2019/08/process-strategy-and-analysis-important.html



Supply chain industrial engineering can be done by industrial engineers from IE department or by being posted in supply chain departments. Supply chain industrial engineering can be part of supplier development activity.


Productivity and Efficiency Improvement in Supply Chain Partner activities is practiced by Toyota Motors.


Toyota Style Industrial Engineering - Waste Elimination - Ohno

"We have eliminated waste by examining available resources, rearranging machines, improving machining processes, installing autonomous systems, improving tools, analyzing transportation methods and optimizing the materials at hand for manufacturing. High production efficiency has also been maintained by preventing the recurrence of defective products, operational mistakes, and accidents, and by incorporating workers' ideas." Taiichi Ohno (P. 21)
https://nraoiekc.blogspot.com/2013/11/taiichi-ohno-on-industrial-engineering.html

For detailed treatment of process industrial engineering applicable to internal manufacturing facilities and supply chain partners' manufacturing facilities go through lessons of:

Process Industrial Engineering FREE ONLINE Course. 

https://nraoiekc.blogspot.com/2020/06/process-industrial-engineering-free.html

Implement Toyota Style Industrial Engineering in Supply Chain


2021

Supply Chain Costing and Performance Management

Gary Cokins, Terry Pohlen, Tom Klammer
John Wiley & Sons, 22-Jun-2021 - Business & Economics - 272 pages

A “how-to” guide for supply chain professionals who need accurate cost information for end-to-end processes

With the increasing pace of globalization, supply chain professionals find that they have less and less margin for error in their decisions making. Competition is getting more intense, and, unfortunately, CFOs and accountants do not currently provide supply chain managers with the information required to make better decisions. Supply Chain Costing and Performance Management, 2nd Edition, will show you (and the executives you report to) how to understand and apply various enterprise and corporate performance management (EPM/CPM) methods related to costs and profit margins and performance measurements.

This book is a “how-to” guide to assist supply chain managers and employee teams to obtain interenterprise cost information on supply chain processes. It provides techniques for obtaining accurate cost and performance information on the activities performed within your firm and on activities performed by trading partners. The techniques and approaches in this book were developed from supply chain costing practices implemented by leading-edge firms. You will learn how you can gain access to reasonably accurate costs and profit margins involved with suppliers, products, stock keeping units (SKUs), service-lines, channels, and customers. In addition, you will gain insight into the activity costs in end-to-end business processes, including the “drivers” for each type of cost.

Learn how to access accurate cost and pricing information related to both your company and your trading partners.

Overcome siloed information by creating your own costing practices using proven methods drawn from leading firms.

Understand what drives activity costs for each step in end-to-end business processes

Assess the performance of your costing activities with step-by-step measurement guidelines

Make better decisions and improve performance and profitability with clearer, more transparent cost and price data

The information in this book will empower supply chain managers with the ability to make better decisions and improve their organizations’ performance and profitability.

2020


Chapter 9. Supplier Management and Development: Creating a World-Class Supply Base

in Purchasing & Supply Chain Management, 7th Edition
Robert M. Monczka, Robert B. Handfield, Larry C. Giunipero, James L. Patterson
Cengage Learning, 2020

2nd Edition Link

8 November 2020



SUPPLIER MANAGEMENT–BENEFITS, PROCESS, & BEST PRACTICES
By Jijnyasa Patowarya In Supplier Management Dec 13th, 2018



Research Article | Open Access
Volume 2016 |Article ID 8641702 | https://doi.org/10.1155/2016/8641702
Strategy for Improving Efficiency of Supply Chain Quality Management in Buyer-Supplier Dyads: The Suppliers’ Perspective
Hyun Jung Kim,1 Jiyoon Son,2 and Soo Wook Kim2
Mathematical Problems in Engineering / 2016

Supplier quality improvement: The value of information under uncertainty
John Quigley Lesley Walls Güven Demirel Bart L.MacCarthy Mahdi Parsa
European Journal of Operational Research
Volume 264, Issue 3, 1 February 2018, Pages 932-947

3 Supplier Management Strategies That Drive Results

Research and Practical Issues of Enterprise Information Systems II pp 717-726| 
A Model of Lean Supplier Management Based on the Lean Production

Improve Vendor Quality Control
By F. Curtis Barry & Company

Managing Supplier Involvement in Process Improvement in Manufacturing
Michael A. McGinnis  Rafeekh Mele Vallopra
Journal of Supply Chain Management, Volume 37, Issue 2, June 2001, Pages 48-53
First published: 05 April 2006 https://doi.org/10.1111/j.1745-493X.2001.tb00105.x

Open access peer-reviewed chapter
Supply Chain Quality Management
By Lynn A. Fish
Published: August 1st 2011
DOI: 10.5772/19973

Vendor and Clients: Integrating Process Improvement Efforts across Both Sides of a Strategic Partner Relationship (Part 1)
James Thompson
10/27/2009

Supplier Development - A Strategy for Improvement
Purchasing and Supply Chain Management
2015
By Robert M. Monczka, Robert B. Handfield, Larry C. Giunipero, James L. Patterson

Supplier quality development: A review of literature and industry practices
Khosrow Noshad & Anjali Awasthi
International Journal of Production Research 
Volume 53, 2015 - Issue 2
Pages 466-487



5 September 2020






2019

What makes a Supply Chain leader?

These organizations prioritize their value chains, ensuring that the supply chain and its related functions are fully integrated with organizational strategy.

A focus on the customer

Visibility through networks of suppliers and partners

Effectiveness and Efficiency (Sustainable) practices in design, manufacturing and delivery.
https://www.sap.com/cmp/dg/supply-chain-leaders/index.html

______________

 
 13 June 2019
______________


SAP Design Module
______________



SAP Design Module Playlist
https://www.youtube.com/watch?v=_I0MnfCMkbQ&list=PL00ZizFAuhWshhrvZfOdlnPe0H_BMXieB
______________

Proposal for Supply Chain Industrial Engineering


Presentation made in a seminar "Recent Trends in Industrial Engineering" organized by  National Institute of Technology, Surat and IIIE Chapter Surat on 6 April 2013.


Part 2
Supply Chain Industrial Engineering
7 Apr 2013
_______________

________________


Part 1
Supply Chain - Industrial Engineering Tools and Techniques
7 Apr 2013
_______________

_______________


_______________

Toyota Supply Chain Management
https://www.youtube.com/watch?v=IRb4yOKrzs0
_______________


Supply Chain Engineering - What is it?
https://thesupplychainengineer.com/supply-chain-engineering-2/

How to Apply IE Techniques in SCM to Reduce Cost and Cut Wastage
Vincent Cheung, M.Phil (IE) BPS Global, 2009 Presentation
http://www.bps-group.net/download/CILT_Seminar_in_Singapore_4_Nov_09.pdf

Supply Chain  - Open Access Book Edited by Vedran Kordic
D. Giglio and R. Minciardi, “Modelling and Optimization of Multi-Site Production Systems in Supply Chain Networks,” Proceedings of the 2003 IEEE International Conference

Y. S. Li, F. F. Ye, Z. M. Fang, and J. G. Yang, “Flexible Supply Chain Optimization and Its SRT Analysis,” Industrial Engineering and Management, vol. 10, no. 1, February 2005, Springer-Verlag, China, pp. 89-93.
Steve Hopper, Supply Chain Industrial Engineer
http://www.linkedin.com/in/SteveHopper


Measurement of Supply Chain Performance

Measuring Supply Chain Performance
Benita M. Beamon
1999 paper
ftp://ftpserv.uncc.edu/coba/mbad/cooper/mbad6208_Spring10/class13(current)/ReadingsReDesign/SCPerformance(Beamon).pdf
( Cost is given as one dimension and responsiveness is given as the other dimension. )

Performance Assessment of Supply Chain Management: A Balanced Scorecard Approach
Computers and Industrial Engineering 2007 - Paper
http://kertogral.etu.edu.tr/SCM_performance_measurement_balanced_score_card_2007_CAIE.pdf
( In internal perspective to promote efficiency and effectiveness in our business processes is given as the mission )


Planing Supply Chain - System Design and Operations Planning
Measurements Provided by Industrial Engineering Discipline/Departments


Controlling Supply Chain
Measurements Provided by IED and Actions Initiated by IED




Scott Stephens, Craig Gustin, and Jim Ayers, "Reengineering the Supply Chain
- The Next Hurdle,"  Information Strategy: The Executive's Journal, Fall 1997, pp. 13-18

The authors said improvements have to be extended to the supply partners. It is not any more sufficient to improve internal operations of a company.

Supply Chain Efficiency - Supply Chain Waste Elimination -





Supply Chain Efficiency - Concept and Measures


Exploring Efficiency and Effectiveness in the Supply Chain - Conceptual Analysis
http://impgroup.org/uploads/papers/4670.pdf

Measurement of Efficiency in a Supply Chain'
Doctoral Thesis
http://pure.ltu.se/portal/files/2331159/LTU-LIC-0851-SE.pdf


Supply Chain Responsiveness and Efficiency – Complementing or Contradicting Each Other?
http://www.systemdynamics.org/conferences/2006/proceed/papers/MINNI308.pdf

Measuring Supply Chain Efficiency - DEA Approach
Indian Pharma Industry - 2012 paper
http://www.joscm.com.br/download/JOSCM_VOL5_NUMBER1_4.pdf



Ilsuk Kim, Hokey Min, (2011) "Measuring supply chain efficiency from a green perspective", Management Research Review, Vol. 34 Iss: 11, pp.1169 - 1189
http://www.emeraldinsight.com/journals.htm?articleid=1959373

Measuring Supply Chain Efficiency and Congestion - DEA approach - Shipping
2003
http://www.engineeringletters.com/issues_v18/issue_4/EL_18_4_08.pdf

How SCOR Model Enhances Global Supply Chain Efficiency and Effectiveness
http://ihome.ust.hk/~al_mtm/files/How_SCOR_Model_Enhance_Global_Supply_Chain_Efficiency_Effectiveness.pdf

An Approach towards Overall Supply Chain Efficiency - MS Thesis 2002
https://gupea.ub.gu.se/bitstream/2077/2360/1/gbs_thesis_2002_29.pdf

Lean Supply Chain

Lean supply chain. The aim is to reduce the total cost of the supply chain-removing waste and creating the most value for the customer.


Improving Supply Chain Efficiency


Combining Lean and Agile Supply Chain - 2011 Paper
http://www.academicjournals.org/ajbm/PDF/pdf2011/4Sept/Banihashemi.pdf

Supply Chain Cost Reduction - Book by Amacom
http://nraomtr.blogspot.in/2011/11/supply-chain-cost-reduction.html

Lean Supply Chain - Concept, Development and Design


Lean Thinking for the Supply Chain
Tompkins
http://www.tompkinsinc.com/article/2004/lean-thinking-supply-chain/

Seven Steps to Building a Lean Supply Chain
Mandyam M. Srinivasan
Mandyam M. Srinivasan is The Ball Corporation Distinguished Professor of Business at the University of Tennessee. He is the author of the book, Streamlined: 14 Principles for Building and Managing the Lean Supply Chain.
http://www.industryweek.com/planning-amp-forecasting/goal-lean-supply-chain


From Lean Manufacturing to Lean Supply Chain: A Foundation for Change
2004 Paper by Lawson, USA
http://swe.lawson.com/www/resource.nsf/pub/Lawson_Whitepaper_2_A4_LowRes.pdf/$FILE/Lawson_Whitepaper_2_A4_LowRes.pdf

Understanding the Lean Supply Chain - Beginning the Journey
2005 Report on Lean Practices in  Supply Chain
APICS - ORACLE - Georgia Southern University
http://coba.georgiasouthern.edu/centers/lit/oracle_WP_supply_chain_r6.pdf


Lean practices in the supply Chain - 2008 Survey
Jones Long LaSalle Report - with participation of APICS, Georgia Tech, and Supply Chain Visions
http://www.joneslanglasalle.com/Documents/JLL-LeanPracticesInSupplyChain.pdf


Lean in Supply Chain Planning  - 2011 Report
Cap Gemini
http://www.capgemini.com/m/en/tl/Lean_in_Supply_Chain_Planning.pdf


Lean Supply Chain Road Map - Book Chapter - McGraw-Hill - 2011
http://www.mhprofessional.com/downloads/products/0071771212/0071771212_ch01.pdf

http://logistics.about.com/od/supplychainintroduction/a/Lean_SCM.htm


Webinars by Georgia Tech
Becoming a Lean Supply Chain Professional - Episode 1
Becoming a Lean Supply Chain Professional - Episode 2
https://www.scl.gatech.edu/resources/whitepapers

https://logistics.gatech.pa/en/education/courses#warehouse-layout




Analytics and Risk Management for Supply Chain Efficiency
http://www.verisk.com/Verisk-Review/Articles/Analytics-and-Risk-Management-for-Supply-Chain-Efficiency.html

From Supply to Demand Chain Management: Efficiency and Customer Satisifaction
2002 - JOM article
http://info.cba.ksu.edu/sheu/MANGT662/MT662_SC%20Reading/Demand%20chain%20Heikkila.pdf


USING SUPPLY CHAIN EFFICIENCY IN PORTFOLIO SELECTION
http://asbbs.org/files/2011/ASBBS2011v1/PDF/F/Farahbod.pdf


___________________

Supply Chain Efficiency - Company News and Reports


Unilever supply chain efficiency, 2009
http://www.logisticsit.com/articles/2009/05/05/4342-unilever-supply-chain


Supply Chain Software


SunSmart Global Inc., an ISO 9001:2015 Certified Multinational Software Corporation incorporated in 2004. SunSmart is headquartered in Silicon Valley, USA and has offices in the UK, Europe, Middle East, India and Far East. SunSmart has more than 3000+ man years of Software Solutions & Services experience in the business verticals of Banking, Financial Services, Securities, Insurance, Government, Retail, Healthcare, Manufacturing and Education.
Products
CRM Software
ERP Software
Asset Management Software
HRMS Software
Procurement Management Software
https://www.sunsmartglobal.com/about-us/


Updated on 18.9.2024, 29.7.2024,  6.5.2022,  12.1.2022,  21.12.2021,  10 July 2020,   28 June 2020, 16 February 2020
First posted on 25 September 2012
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