Marek Bankiir, Leanway
Ettekanne 12.08.2021 konverentsil "Mööblitööstuse väljakutsed 2021"
Korraldajad: Võrumaa KHK kompetentsikeskus TSENTER ja Kagu-Eesti puiduklaster
Konverentsi info https://tsenter.ee/sundmused/mooblitoostuse-valjakutsed-2021/
This document discusses process validation for injection molding and provides guidance on key challenges and statistical methods to address them. It covers establishing a process window through design of experiments (DOE) to understand significant variables. Measurement system analysis (MSA) is discussed to ensure reliable measurements. The document emphasizes using adequate sample sizes and applying statistical confidence levels when assessing process capability to minimize risk. The overarching message is to consider product and patient risk, focus on intended outcomes, and avoid jumping to conclusions without proper statistical analysis.
This document provides an overview of supply chain design and operations presented by Anqi Guo. It discusses where the presenter obtained their background from, including education and past clients. The content covers introductions to operations research and its applications in supply chain design. Case studies are presented on revitalizing a manufacturing company, designing a bike rental system, and improving a pharmacy supply chain for distributing antiviral drugs. Brief details are given on Amazon's use of algorithms to predict and stock popular products before customer orders.
Rob Baarda - Are Real Test Metrics Predictive for the Future?TEST Huddle
EuroSTAR Software Testing Conference 2008 presentation on Are Real Test Metrics Predictive for the Future? by Rob Baarda. See more at conferences.eurostarsoftwaretesting.com/past-presentations/
In this Dagstuhl talk, I presented my current research on cloud auto-scaling and component connector self-adaptation and how I employed type-2 fuzzy control to tame the uncertainty regarding knowledge specification.
Autonomic Resource Provisioning for Cloud-Based SoftwarePooyan Jamshidi
This document proposes using fuzzy logic and type-2 fuzzy sets to develop an autonomous resource provisioning system for cloud-based software. Current auto-scaling solutions have limitations including requiring deep application knowledge and performance modeling expertise from users. The proposed system would use fuzzy inference to map monitored performance data to scaling actions, eliminating the need for users to specify scaling parameters or policies. It would incorporate uncertainty into the modeling and use expert knowledge from multiple users to develop robust and adaptive provisioning behavior.
The document defines a lean assessment for a manufacturing process. It includes categories like inventory, teams, processes, maintenance, layout, suppliers, setups, quality, and scheduling. For each category there are questions to rate aspects on a scale. The results of the assessment show opportunities for improvement in scheduling, layout, and quality. An analysis identifies gaps such as converting to a pull system with supermarkets and kanbans, and improving assembly productivity through cell design.
Manufacturing's Holy Grail: A Practical Science for Executives and ManagersUBMCanon
Mark Spearman, President and CEO, Factory Physics
In this session we will discuss:
-Manufacturing Myths that Muddle Management:
-Bottlenecks and non-bottlenecks—meeting demand
-One Piece Flow—what is the real cost?
-ABC Inventory Policies—how low can you go?
And many more!
Mark L. Spearman is President and CEO of Factory Physics, Inc., a firm that provides management consulting, training, and software to improve manufacturing and supply chain management. In his former life as an academic, he was Head of the Department of Industrial and Systems Engineering at Texas A&M University and also a professor at Georgia Tech and Northwestern University. He is coauthor, with Wallace J. Hopp, of the book, “Factory Physics” that was named the IIE Book of the Year. He has helped more than one hundred companies over the last twenty five years apply the principles of factory physics to improve operations by increasing productivity, reducing cycle times and inventories by developing integrated supply chain approaches that are both simple and effective.
This document discusses process validation for injection molding and provides guidance on key challenges and statistical methods to address them. It covers establishing a process window through design of experiments (DOE) to understand significant variables. Measurement system analysis (MSA) is discussed to ensure reliable measurements. The document emphasizes using adequate sample sizes and applying statistical confidence levels when assessing process capability to minimize risk. The overarching message is to consider product and patient risk, focus on intended outcomes, and avoid jumping to conclusions without proper statistical analysis.
This document provides an overview of supply chain design and operations presented by Anqi Guo. It discusses where the presenter obtained their background from, including education and past clients. The content covers introductions to operations research and its applications in supply chain design. Case studies are presented on revitalizing a manufacturing company, designing a bike rental system, and improving a pharmacy supply chain for distributing antiviral drugs. Brief details are given on Amazon's use of algorithms to predict and stock popular products before customer orders.
Rob Baarda - Are Real Test Metrics Predictive for the Future?TEST Huddle
EuroSTAR Software Testing Conference 2008 presentation on Are Real Test Metrics Predictive for the Future? by Rob Baarda. See more at conferences.eurostarsoftwaretesting.com/past-presentations/
In this Dagstuhl talk, I presented my current research on cloud auto-scaling and component connector self-adaptation and how I employed type-2 fuzzy control to tame the uncertainty regarding knowledge specification.
Autonomic Resource Provisioning for Cloud-Based SoftwarePooyan Jamshidi
This document proposes using fuzzy logic and type-2 fuzzy sets to develop an autonomous resource provisioning system for cloud-based software. Current auto-scaling solutions have limitations including requiring deep application knowledge and performance modeling expertise from users. The proposed system would use fuzzy inference to map monitored performance data to scaling actions, eliminating the need for users to specify scaling parameters or policies. It would incorporate uncertainty into the modeling and use expert knowledge from multiple users to develop robust and adaptive provisioning behavior.
The document defines a lean assessment for a manufacturing process. It includes categories like inventory, teams, processes, maintenance, layout, suppliers, setups, quality, and scheduling. For each category there are questions to rate aspects on a scale. The results of the assessment show opportunities for improvement in scheduling, layout, and quality. An analysis identifies gaps such as converting to a pull system with supermarkets and kanbans, and improving assembly productivity through cell design.
Manufacturing's Holy Grail: A Practical Science for Executives and ManagersUBMCanon
Mark Spearman, President and CEO, Factory Physics
In this session we will discuss:
-Manufacturing Myths that Muddle Management:
-Bottlenecks and non-bottlenecks—meeting demand
-One Piece Flow—what is the real cost?
-ABC Inventory Policies—how low can you go?
And many more!
Mark L. Spearman is President and CEO of Factory Physics, Inc., a firm that provides management consulting, training, and software to improve manufacturing and supply chain management. In his former life as an academic, he was Head of the Department of Industrial and Systems Engineering at Texas A&M University and also a professor at Georgia Tech and Northwestern University. He is coauthor, with Wallace J. Hopp, of the book, “Factory Physics” that was named the IIE Book of the Year. He has helped more than one hundred companies over the last twenty five years apply the principles of factory physics to improve operations by increasing productivity, reducing cycle times and inventories by developing integrated supply chain approaches that are both simple and effective.
Need for Speed: How to Performance Test the right way by Annie BhaumikQA or the Highway
This document discusses the importance of performance testing web applications. It notes that 53% of users will abandon a website if it takes over 3 seconds to load, and 79% of those users will not return. The document outlines different types of performance tests including load testing, endurance testing, spike testing, and stress testing. It emphasizes the need for performance testing to be realistic by simulating real user behavior, network conditions, workloads and data volumes similar to the production environment. The document also discusses analyzing test results and key performance indicators to understand how the system performs under different loads and over time.
This document provides an overview of Overall Equipment Effectiveness (OEE). OEE is a metric used to measure manufacturing system performance by calculating availability, performance, and quality rates. It identifies the gap between actual and maximum potential output. The document discusses the "six big losses" that reduce OEE - breakdowns, setups, minor stoppages, speed losses, defects, and start-up waste. Tracking OEE can help companies increase productivity 10-50% and profits 20-300% by prioritizing issues and driving continuous improvement.
This case study describes how MTM tools and Lean principles were used to improve the efficiency of an outdoor cooking appliance production line. The production line originally had 4 operators working in separate workstations with significant wait times. MTM analysis was used to measure task times and identify opportunities. The line was rebalanced into a U-shape with tasks grouped by zone. Operators now push carts between zones, completing full product cycles. This reduced waste and improved flexibility. MTM databases were created to standardize times and enable balancing for new products. The result was a 99.6% balanced line with 4 operators, increasing productivity by 34.68%.
This document provides an overview of process capability and how to calculate it. Process capability is a measurement of how well a process is performing compared to customer requirements. It is calculated by collecting process data, checking if the data is normally distributed, and using formulas to determine metrics like Cp, Cpk which indicate if the process mean and variability are able to meet specifications. If a process is found to be incapable, actions would be taken like process improvement projects to address performance gaps.
The document discusses validation and calibration of equipment used in the pharmaceutical industry. It defines validation as establishing evidence that a process will consistently produce quality products. Calibration ensures instrument readings are accurate by comparing them to standards. The FDA provides guidelines for validation. Key equipment discussed include tablet presses, dissolution apparatus, friability equipment, balances, and stability chambers. Specifications and operating parameters are provided for each.
This document discusses applying lean principles to optimize the production system design for a fishing net manufacturing company. It identifies key controllable factors like production unit size, pacemaker process, order batching, and production sequence. Through simulation and optimization, it evaluates different scenarios and identifies an optimal future state design that increases service level from 68% to 90% while decreasing work-in-process from 63,971 kg to 42,269 kg. This future state map can help the company implement lean manufacturing practices with no additional investment needed.
The document discusses challenges with current rule-based approaches to elasticity management in cloud applications and proposes a decentralized autonomous solution. It notes that rule-based systems require defining optimal thresholds upfront and do not scale well to large applications. The proposed approach uses reinforcement learning to allow instances to autonomously share load during critical events without a centralized controller. This could enable better placements of applications across instances and more efficient scaling decisions in dynamic cloud environments.
This document discusses self-learning cloud controllers that can dynamically scale cloud resources. It notes that current auto-scaling approaches require deep application knowledge and expertise to determine scaling parameters and policies. The paper proposes a type-2 fuzzy logic approach called RobusT2Scale that uses fuzzy rules and monitoring data to determine scaling actions. It aims to handle uncertainty in elastic systems and accommodate different user preferences through fuzzy reasoning over workload and response time data. The approach pre-computes scaling decisions to enable efficient runtime elasticity control. It is evaluated based on its ability to meet an SLA target response time compared to over- and under-provisioning approaches.
Fuzzy Self-Learning Controllers for Elasticity Management in Dynamic Cloud Ar...Pooyan Jamshidi
(1) The document discusses challenges in managing elasticity in cloud architectures due to unpredictable demand and uncertainty in measurements. (2) It proposes a fuzzy self-learning controller called RobusT2Scale that uses type-2 fuzzy logic to qualitatively specify thresholds and make robust scaling decisions despite uncertainty. (3) Experimental results show that RobusT2Scale is able to guarantee service level agreements while avoiding over- and under-provisioning of resources compared to other approaches.
This document discusses process capability and measurement indices. It defines common and assignable causes of variation, and explains how to measure a process by taking samples and analyzing the resulting distribution. The key metrics for measuring process capability are Cp, which indicates if a process can produce within specifications regardless of the process mean, and Cpk, which also considers how centered the process is within specifications. Examples are provided to demonstrate how to calculate Cp and Cpk. The goal is for these metrics to be above 1 to indicate a capable process.
Production - Reducing Machine Setup Time - IEMGan Chun Chet
The document discusses machine performance and how to improve it. It describes key ratios to understand like the ratio of operating time to setup time. It also discusses performance indicators like machine performance as a percentage. Graphs of performance over time are shown and statistical techniques are presented for monitoring setup times, like finding the average, maximum and minimum. The goal is to understand a machine's capacity to plan ahead and identify opportunities to increase operating hours and performance.
This document summarizes line balancing techniques for optimizing production line efficiency. It discusses calculating standard minute values using time studies and setting production targets. Pitch time and control limits are explained to balance the workload across workstations. Bottleneck processes are identified and methods to reduce them are provided, such as work improvement, equipment upgrades, and job reassignment. The overall goal of line balancing is to design a smooth production flow that allows each worker to complete their allotted work within an even time frame.
Lean Six Sigma is a methodology that focuses on reducing waste and variation in processes by improving quality and efficiency. It was developed by combining Lean manufacturing principles with Six Sigma quality measures and has been shown to be effective at improving processes in manufacturing and healthcare. The methodology uses structured problem solving techniques and statistical tools to optimize processes and reduce defects, variation, and waste to better meet customer needs.
The document discusses a case study involving the evaluation of a measurement system for an important quality variable, CTQ1, at W.R. Grace. A measurement systems analysis (MSA) study was conducted involving the four worldwide sites that produce the raw material. The results showed a high %GR&R of 94.3% and P/T ratio of 116%, indicating significant measurement error. When analyzed separately, the sites showed varying levels of measurement capability, with one site having a %GR&R of 38.9%. The MSA study identified opportunities to improve the measurement system and link it back to process improvements.
This document provides sample questions that may appear on an OPS 571 final exam, covering topics like supply chain classification, economic order quantity, production planning strategies, forecasting, problem definition frameworks, project management using critical path method, inventory management models, lean production concepts, learning curves, process quality monitoring charts, queuing systems, operations design, productivity metrics, and theory of constraints. It contains over 50 multiple choice questions testing knowledge of these operations and supply chain management topics.
presentation of simulation methods using monte carlo and an explanation of simulation methods in production in companies, this presentation is suitable for students and lecturers in the department of production management and marketing, industrial engineering etc.
This document discusses key concepts related to production line management including:
Standard minute value (SMV) which represents the average time for a worker to complete a task including allowances. Target calculation uses SMV to determine production goals.
Line balancing aims to match production rate to takt time by balancing operator and machine times.
A bottleneck refers to the lowest output point in the production line.
Other topics covered include line feeding activities from pre-setting to monitoring production, and how to address issues like re-balancing the line and improving efficiency over time.
A Framework for Robust Control of Uncertainty in Self-Adaptive Software Conn...Pooyan Jamshidi
We enable reliable and dependable self‐adaptations of component connectors in unreliable environments with imperfect monitoring facilities and conflicting user opinions about adaptation policies by developing a framework which comprises: (a) mechanisms for robust model evolution, (b) a method for adaptation reasoning, and (c) tool support that allows an end‐to‐end application of the developed techniques in real‐world domains.
This document provides sample questions that may appear on an OPS 571 final exam. It includes over 50 multiple choice questions covering topics like supply chain management, production planning, inventory management, project management, quality control, and operations strategy. The questions assess understanding of concepts like EOQ, CPM, queuing theory, lean production, and theory of constraints.
This document discusses predictive maintenance and how to develop predictive maintenance algorithms using MATLAB. It defines predictive, preventative, and reactive maintenance. It then outlines the steps to develop a predictive algorithm, including acquiring sensor data, preprocessing the data, identifying condition indicators, training a model, and deploying the model. It provides examples of developing algorithms for fault classification and remaining useful life estimation using sensor data from a triplex pump.
Need for Speed: How to Performance Test the right way by Annie BhaumikQA or the Highway
This document discusses the importance of performance testing web applications. It notes that 53% of users will abandon a website if it takes over 3 seconds to load, and 79% of those users will not return. The document outlines different types of performance tests including load testing, endurance testing, spike testing, and stress testing. It emphasizes the need for performance testing to be realistic by simulating real user behavior, network conditions, workloads and data volumes similar to the production environment. The document also discusses analyzing test results and key performance indicators to understand how the system performs under different loads and over time.
This document provides an overview of Overall Equipment Effectiveness (OEE). OEE is a metric used to measure manufacturing system performance by calculating availability, performance, and quality rates. It identifies the gap between actual and maximum potential output. The document discusses the "six big losses" that reduce OEE - breakdowns, setups, minor stoppages, speed losses, defects, and start-up waste. Tracking OEE can help companies increase productivity 10-50% and profits 20-300% by prioritizing issues and driving continuous improvement.
This case study describes how MTM tools and Lean principles were used to improve the efficiency of an outdoor cooking appliance production line. The production line originally had 4 operators working in separate workstations with significant wait times. MTM analysis was used to measure task times and identify opportunities. The line was rebalanced into a U-shape with tasks grouped by zone. Operators now push carts between zones, completing full product cycles. This reduced waste and improved flexibility. MTM databases were created to standardize times and enable balancing for new products. The result was a 99.6% balanced line with 4 operators, increasing productivity by 34.68%.
This document provides an overview of process capability and how to calculate it. Process capability is a measurement of how well a process is performing compared to customer requirements. It is calculated by collecting process data, checking if the data is normally distributed, and using formulas to determine metrics like Cp, Cpk which indicate if the process mean and variability are able to meet specifications. If a process is found to be incapable, actions would be taken like process improvement projects to address performance gaps.
The document discusses validation and calibration of equipment used in the pharmaceutical industry. It defines validation as establishing evidence that a process will consistently produce quality products. Calibration ensures instrument readings are accurate by comparing them to standards. The FDA provides guidelines for validation. Key equipment discussed include tablet presses, dissolution apparatus, friability equipment, balances, and stability chambers. Specifications and operating parameters are provided for each.
This document discusses applying lean principles to optimize the production system design for a fishing net manufacturing company. It identifies key controllable factors like production unit size, pacemaker process, order batching, and production sequence. Through simulation and optimization, it evaluates different scenarios and identifies an optimal future state design that increases service level from 68% to 90% while decreasing work-in-process from 63,971 kg to 42,269 kg. This future state map can help the company implement lean manufacturing practices with no additional investment needed.
The document discusses challenges with current rule-based approaches to elasticity management in cloud applications and proposes a decentralized autonomous solution. It notes that rule-based systems require defining optimal thresholds upfront and do not scale well to large applications. The proposed approach uses reinforcement learning to allow instances to autonomously share load during critical events without a centralized controller. This could enable better placements of applications across instances and more efficient scaling decisions in dynamic cloud environments.
This document discusses self-learning cloud controllers that can dynamically scale cloud resources. It notes that current auto-scaling approaches require deep application knowledge and expertise to determine scaling parameters and policies. The paper proposes a type-2 fuzzy logic approach called RobusT2Scale that uses fuzzy rules and monitoring data to determine scaling actions. It aims to handle uncertainty in elastic systems and accommodate different user preferences through fuzzy reasoning over workload and response time data. The approach pre-computes scaling decisions to enable efficient runtime elasticity control. It is evaluated based on its ability to meet an SLA target response time compared to over- and under-provisioning approaches.
Fuzzy Self-Learning Controllers for Elasticity Management in Dynamic Cloud Ar...Pooyan Jamshidi
(1) The document discusses challenges in managing elasticity in cloud architectures due to unpredictable demand and uncertainty in measurements. (2) It proposes a fuzzy self-learning controller called RobusT2Scale that uses type-2 fuzzy logic to qualitatively specify thresholds and make robust scaling decisions despite uncertainty. (3) Experimental results show that RobusT2Scale is able to guarantee service level agreements while avoiding over- and under-provisioning of resources compared to other approaches.
This document discusses process capability and measurement indices. It defines common and assignable causes of variation, and explains how to measure a process by taking samples and analyzing the resulting distribution. The key metrics for measuring process capability are Cp, which indicates if a process can produce within specifications regardless of the process mean, and Cpk, which also considers how centered the process is within specifications. Examples are provided to demonstrate how to calculate Cp and Cpk. The goal is for these metrics to be above 1 to indicate a capable process.
Production - Reducing Machine Setup Time - IEMGan Chun Chet
The document discusses machine performance and how to improve it. It describes key ratios to understand like the ratio of operating time to setup time. It also discusses performance indicators like machine performance as a percentage. Graphs of performance over time are shown and statistical techniques are presented for monitoring setup times, like finding the average, maximum and minimum. The goal is to understand a machine's capacity to plan ahead and identify opportunities to increase operating hours and performance.
This document summarizes line balancing techniques for optimizing production line efficiency. It discusses calculating standard minute values using time studies and setting production targets. Pitch time and control limits are explained to balance the workload across workstations. Bottleneck processes are identified and methods to reduce them are provided, such as work improvement, equipment upgrades, and job reassignment. The overall goal of line balancing is to design a smooth production flow that allows each worker to complete their allotted work within an even time frame.
Lean Six Sigma is a methodology that focuses on reducing waste and variation in processes by improving quality and efficiency. It was developed by combining Lean manufacturing principles with Six Sigma quality measures and has been shown to be effective at improving processes in manufacturing and healthcare. The methodology uses structured problem solving techniques and statistical tools to optimize processes and reduce defects, variation, and waste to better meet customer needs.
The document discusses a case study involving the evaluation of a measurement system for an important quality variable, CTQ1, at W.R. Grace. A measurement systems analysis (MSA) study was conducted involving the four worldwide sites that produce the raw material. The results showed a high %GR&R of 94.3% and P/T ratio of 116%, indicating significant measurement error. When analyzed separately, the sites showed varying levels of measurement capability, with one site having a %GR&R of 38.9%. The MSA study identified opportunities to improve the measurement system and link it back to process improvements.
This document provides sample questions that may appear on an OPS 571 final exam, covering topics like supply chain classification, economic order quantity, production planning strategies, forecasting, problem definition frameworks, project management using critical path method, inventory management models, lean production concepts, learning curves, process quality monitoring charts, queuing systems, operations design, productivity metrics, and theory of constraints. It contains over 50 multiple choice questions testing knowledge of these operations and supply chain management topics.
presentation of simulation methods using monte carlo and an explanation of simulation methods in production in companies, this presentation is suitable for students and lecturers in the department of production management and marketing, industrial engineering etc.
This document discusses key concepts related to production line management including:
Standard minute value (SMV) which represents the average time for a worker to complete a task including allowances. Target calculation uses SMV to determine production goals.
Line balancing aims to match production rate to takt time by balancing operator and machine times.
A bottleneck refers to the lowest output point in the production line.
Other topics covered include line feeding activities from pre-setting to monitoring production, and how to address issues like re-balancing the line and improving efficiency over time.
A Framework for Robust Control of Uncertainty in Self-Adaptive Software Conn...Pooyan Jamshidi
We enable reliable and dependable self‐adaptations of component connectors in unreliable environments with imperfect monitoring facilities and conflicting user opinions about adaptation policies by developing a framework which comprises: (a) mechanisms for robust model evolution, (b) a method for adaptation reasoning, and (c) tool support that allows an end‐to‐end application of the developed techniques in real‐world domains.
This document provides sample questions that may appear on an OPS 571 final exam. It includes over 50 multiple choice questions covering topics like supply chain management, production planning, inventory management, project management, quality control, and operations strategy. The questions assess understanding of concepts like EOQ, CPM, queuing theory, lean production, and theory of constraints.
This document discusses predictive maintenance and how to develop predictive maintenance algorithms using MATLAB. It defines predictive, preventative, and reactive maintenance. It then outlines the steps to develop a predictive algorithm, including acquiring sensor data, preprocessing the data, identifying condition indicators, training a model, and deploying the model. It provides examples of developing algorithms for fault classification and remaining useful life estimation using sensor data from a triplex pump.
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This document provides information about HOUFEK a.s., a leading manufacturer of woodworking machines in Europe. It was founded in 1991 in the Czech Republic and currently produces around 1,000 machines per year for over 50 countries. The document discusses several CNC woodworking machine models produced by HOUFEK including the CNC Orion, CNC Mercury, CNC Scorpion, and CNC Titan. It provides technical specifications and descriptions of each machine model. It also includes information on control systems, worktables, accessories, and HOUFEK's partner in Estonia.
Alari Kulljus
Mikk A. Kulljus
Ettekanne TSENTRI koolitusel "CNC maailma võlud ja valud"
koolituspäeval “CNC maailma võlud ja valud.“
https://tsenter.ee/sundmused/cnc-maai...
Linkedin: https://www.linkedin.com/company/tsen...
Facebook: https://www.facebook.com/tsenter.ee/
Instagram: https://www.instagram.com/tsenterest/
Ettekanne TSENTRI koolituselt "CNC maailma võlud ja valud"
Madis Lepiksaar, Mehhatroonika insener
https://tsenter.ee/sundmused/cnc-maailma-volud-ja-valud/
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Kuidas häid eesmärke sõnastada?
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Best Competitive Marble Pricing in Dubai - ☎ 9928909666Stone Art Hub
Stone Art Hub offers the best competitive Marble Pricing in Dubai, ensuring affordability without compromising quality. With a wide range of exquisite marble options to choose from, you can enhance your spaces with elegance and sophistication. For inquiries or orders, contact us at ☎ 9928909666. Experience luxury at unbeatable prices.
[To download this presentation, visit:
https://www.oeconsulting.com.sg/training-presentations]
This presentation is a curated compilation of PowerPoint diagrams and templates designed to illustrate 20 different digital transformation frameworks and models. These frameworks are based on recent industry trends and best practices, ensuring that the content remains relevant and up-to-date.
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These materials are perfect for enhancing your business or classroom presentations, offering visual aids to supplement your insights. Please note that while comprehensive, these slides are intended as supplementary resources and may not be complete for standalone instructional purposes.
Frameworks/Models included:
Microsoft’s Digital Transformation Framework
McKinsey’s Ten Guiding Principles of Digital Transformation
Forrester’s Digital Transformation Framework
IDC’s Digital Transformation MaturityScape
MIT’s Digital Transformation Framework
Gartner’s Digital Transformation Framework
Accenture’s Digital Strategy & Enterprise Frameworks
Deloitte’s Digital Industrial Transformation Framework
Capgemini’s Digital Transformation Framework
PwC’s Digital Transformation Framework
Cisco’s Digital Transformation Framework
Cognizant’s Digital Transformation Framework
DXC Technology’s Digital Transformation Framework
The BCG Strategy Palette
McKinsey’s Digital Transformation Framework
Digital Transformation Compass
Four Levels of Digital Maturity
Design Thinking Framework
Business Model Canvas
Customer Journey Map
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[To download this presentation, visit:
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Each framework is presented with visually engaging diagrams and templates, ensuring the content is both informative and appealing. While this compilation is thorough, please note that the slides are intended as supplementary resources and may not be sufficient for standalone instructional purposes.
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INCLUDED FRAMEWORKS/MODELS:
1. Stanford’s Design Thinking
2. IDEO’s Human-Centered Design
3. Strategyzer’s Business Model Innovation
4. Lean Startup Methodology
5. Agile Innovation Framework
6. Doblin’s Ten Types of Innovation
7. McKinsey’s Three Horizons of Growth
8. Customer Journey Map
9. Christensen’s Disruptive Innovation Theory
10. Blue Ocean Strategy
11. Strategyn’s Jobs-To-Be-Done (JTBD) Framework with Job Map
12. Design Sprint Framework
13. The Double Diamond
14. Lean Six Sigma DMAIC
15. TRIZ Problem-Solving Framework
16. Edward de Bono’s Six Thinking Hats
17. Stage-Gate Model
18. Toyota’s Six Steps of Kaizen
19. Microsoft’s Digital Transformation Framework
20. Design for Six Sigma (DFSS)
To download this presentation, visit:
https://www.oeconsulting.com.sg/training-presentations
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9. PROLOOG
9
Lean on võlts - kuidas ma saan kauba
vajalikuks hetkeks uksele, kui tellimuse
tähtaeg on keskmiselt kolm nädalat aga
materjalide tarneaeg kolm kuud?
Kui sul on 200 klienti ja 5000 toodet, kuidas
sa saad tootmise hetkeks materjali Hiinast
kohale, kui mõnel “põleb” ja homme oleks
vaja?
15. 100% lao täitmismäär
nii, et ühtegi toodet
laos ei ole
TÄIUSLIK MAAILM - KUI NÕUDLUS JA TRANSFORMATSIOON OLEKSID HARMOONIAS
Esimese korraga
õige tootedisain
100% saadaolev
võimekus täpselt
vajamineval momendil
Täpselt õigel
hetkel ilmuv klient
100%
kvaliteet
Kvaliteet
100%
Ohoo, täpselt
seda vajasingi!
Kuidas sa teadsid?
16. 100% lao täitmismäär
nii, et ühtegi toodet
laos ei ole
TÄIUSLIK MAAILM - KUI NÕUDLUS JA TRANSFORMATSIOON OLEKSID HARMOONIAS
Esimese korraga
õige tootedisain
100% saadaolev
võimekus täpselt
vajamineval momendil
Täpselt õigel
hetkel ilmuv klient
100%
kvaliteet
Kvaliteet
100%
Ohoo, täpselt
seda vajasingi!
Kuidas sa teadsid?
17. 100% lao täitmismäär
nii, et ühtegi toodet
laos ei ole
TÄIUSLIK MAAILM - KUI NÕUDLUS JA TRANSFORMATSIOON OLEKSID HARMOONIAS
Esimese korraga
õige tootedisain
100% saadaolev
võimekus täpselt
vajamineval momendil
Täpselt õigel
hetkel ilmuv klient
100%
kvaliteet
Kvaliteet
100%
Ohoo, täpselt
seda vajasingi!
Kuidas sa teadsid?
18. PUHVRID - MISKI VÕI KEEGI ALATI OOTAB
Varu
valmistooted ootavad
Aeg
klient ootab
Võimekus
masinad või töötajad ootavad
23. VÕIMEKUSE PUHVER - TOYOTA
1.
vahetus
2.
vahetus
3.
vahetus
võimekus-
puhver
•ennetav hooldus
•toodangudefitsiidi katmine
•protsessi täiustamine
24. VÕIMEKUSE PUHVRI PARADOKS - EFEKTIIVSUSE SUURENDAMINE
24
u =
ra
re
ra - arrival rate
re - effective rate
u =
7 tk/h
10 tk/h
= 0,7 ehk 70%
Protsess 1
7 tk/h
10 tk/h
9,5 tk/h
36%
u =
9,5 tk/h
10 tk/h
= 0,95 ehk 95%
Kui u 0,7, siis WIPq =
0,7
1 - 0,7
WIPq =
u
1 - u
= 2,3 tk
Kui u 0,95, siis WIPq =
0,95
1 - 0,95
= 19 tk
0,4
0,7
1
Enne Pärast
95%
70%
36%
Koormatus
0
65
130
Enne Pärast
114
13,8
726%
Läbimisaeg
25. 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Läbimisaeg
Lühike
Pikk
Koormatus
Sir J. F. C. Kingman
KINGMANI VALEM JA SEADUS
26. KINGMANI VALEM JA SEADUS
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Läbimisaeg
Lühike
Pikk
Koormatus
Varieeruvuse suurenemine
(sissetulevate tööde ajaline ebaühtlus, protsessietapi
töötlemisaja variatsioon jne)
Variatsioon Koormatus Töötlemisaeg
WIPq =
c²a
2
c²e
+
×
u
1 - u
× te
27. KINGMANI VALEM JA SEADUS
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Läbimisaeg
Lühike
Pikk
Koormatus
Tänane
tase
VÄHENDA VARIATSIOONI
LISA
VÕIMEKUST
28. KLASSIKALINE ARUSAAM
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% 110% 120% 130%
Läbimisaeg
Lühike
Pikk
Koormatus
Pole teostatav
29. MIS OLEKS OPTIMAALNE KOORMATUSE TASE?
0
1
2
3
4
5
0
2
4
6
8
10
12
14
0 10 20 30 40 50 60
KLIENDINÕUDLUS (9,6 tk/päevas)
Optimaalne
tsoon
Süsteem on
kuival
Süsteem on
ülekoormatud
best-case-performance (TH)
tegelik TH erineva WIP-i juures
best-case-performance (LT)
tegelik LT erineva WIP-i juures
Läbilaskevõime
(ühikuid/päevas)
Läbimisaeg
(päevades)
WIP (tööde/tellimuste hulk süsteemis)
30. NÄIDE: VARIATSIOON (TOOTEARTIKLITE PALJUSUS)
30
u =
Ra = 6tk/min
Re = 8tk/min
= 0,75
WIP =
0,75
1-0,75
= 3
1 min
1 min
1 min
1 min
Ra = 6tk/min
Re = 8tk/min
Te = 7,5 sek/tk
A = 100%
L/T = (7,5 × 3)+7,5 = 30 sek
85%
A
Re = 6,8 tk/min
u =
Ra = 6tk/min
Re = 6,8tk/min
= 0,88
WIP =
0,88
1-0,88
= 7,3
L/T = (8,8 × 7,3)+8,8 = 73 sek
Te =
7,5 sek/tk
0,85 A-määr
= 8,8 sek
7
8
9
100% A 85% A
8,8
7,5
Te
17%
0
25
50
75
100% A 80% A
73
30
L/T
143%
33. KOKKUVÕTE - MILLEGA TULEB ARVESTADA
“Kui töökeskus suurendab koormatust, ilma et teeks muid muudatusi, siis keskmine tööde
hulk süsteemis (WIP) ja läbimisaeg kasvavad suuresti mittelineaarsel moel. Seda
võimendab omakorda süsteemis esinev variatsioon“
“Suurenev variatsioon halvendab alati operatsioonisüsteemi jõudlust ja puhverdatakse
järgmiseks kolmeks võimaluseks: varud, aeg, võimekus.“
35. STRATEEGILISED JA OPERATSIOONILISED EESMÄRGID
35
“Teenida raha täna ja tulevikus viisil, mis on kooskõlas meie
tuumväärtustega“
Tootmisettevõtte fundamentaalne eesmärk:
“Teenida raha täna ja tulevikus“
36. STRATEEGILISED JA OPERATSIOONILISED EESMÄRGID
36
“Saavutada pikaajaliselt hea investeeringute tasuvus (ROI) selliselt, mis on
kooskõlas meie tuumväärtustega“
Tootmisettevõtte fundamentaalne eesmärk:
38. STRATEEGILISED JA OPERATSIOONILISED EESMÄRGID
38
Käive
Varad
Kulud
Kõrgetasemelised
finantsnäitajad
=
Madalaastmelised
operatsioonilised näitajad
Tehase
läbilaskevõime
= Laovaru
=
Op. väljaminekud
(ületunnid, praak
jne)
39. STRATEEGILISED JA OPERATSIOONILISED EESMÄRGID
39
Hea
investeeringu
tasuvus (ROI)
Suur kasum
Minimaalsed
varad
ROI =
kasum
varad
Madalad
kulud
Suur müük
Kõrge
koormatus
Väikesed
varud
Madal ühiku
kulu
Väiksem
variatiivsus
Madal hind
Kvaliteetne
toode
Kõrge
teenustase
Kiire
reageering
Palju tooteid
Lühike
läbimisaeg
Madal
koormatus
Suured
varud
Suurem
variatiivsus
Suur läbi-
laskevõime
Kõrge
koormatus
Väikesed
varud
Väiksem
variatiivsus
40. STRATEEGILISED JA OPERATSIOONILISED EESMÄRGID
40
Hea
investeeringu
tasuvus (ROI)
Suur kasum
Minimaalsed
varad
ROI =
kasum
varad
Madalad
kulud
Suur müük
Kõrge
koormatus
Väikesed
varud
Madal ühiku
kulu
Väiksem
variatiivsus
Madal hind
Kvaliteetne
toode
Kõrge
teenustase
Kiire
reageering
Palju tooteid
Lühike
läbimisaeg
Madal
koormatus
Suured
varud
Suurem
variatiivsus
Suur läbi-
laskevõime
Kõrge
koormatus
Väikesed
varud
Väiksem
variatiivsus
41. STRATEEGILISED JA OPERATSIOONILISED EESMÄRGID
41
Kulud
Kvaliteet
Ebatõhus
Võimatu
Madalad
Kõrged
Madal Kõrge
Kulud
Kiirus
Ebatõhus
Võimatu
Madalad
Kõrged
Aeglane Kiire
Kulud
Variatiivsus
Ebatõhus
Võimatu
Madalad
Kõrged
Madal Kõrge
Madalad
Kõrged
Suurem
personaalsus
Väiksem
personaalsus
Kulud
Teenus
Ebatõhus
Võimatu
46. STRATEEGILISED JA OPERATSIOONILISED EESMÄRGID
46
Kulud
Kvaliteet
Ebatõhus
Võimatu
Madalad
Kõrged
Madal Kõrge
Kulud
Kiirus
Ebatõhus
Võimatu
Madalad
Kõrged
Aeglane Kiire
Kulud
Variatiivsus
Ebatõhus
Võimatu
Madalad
Kõrged
Madal Kõrge
Madalad
Kõrged
Suurem
personaalsus
Väiksem
personaalsus
Kulud
Teenus
Ebatõhus
Võimatu
46
47. JUHI VALIKUD
Tegeleda iga päev
lõputu kaosega
1
Kopeerida teiste
lahendusi ja loota, et
need töötavad
2
Luua teadusel baseeruv
operatsioonisüsteem, mis
järgib äristrateegiat
3
49. EPILOOG
49
Lean on võlts - kuidas ma saan kauba
vajalikuks hetkeks uksele, kui tellimuse
tähtaeg on keskmiselt kolm nädalat aga
materjalide tarneaeg kolm kuud?
Kui sul on 200 klienti ja 5000 toodet, kuidas
sa saad tootmise hetkeks materjali Hiinast
kohale, kui mõnel “põleb” ja homme oleks
vaja?