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rom abaqus import * imports the abaqus module and creates references to aB puhlic~oots . ..defined by that module.

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is for making t~e symbolic constants defined by the Abaqus Scripting Interface available to the script. What are symbolic constants? They are variables with a constant value (hence the term constant) that have been given a nanie that makes more sense to a user (hence the term symbolic) but have some meaning to Abaqus.

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We use symbolic constants in the sc'ript. Look at the relevant lines in the script where the part is created. Notice the statement: beamPart=beamModel.Part(name='Beam', dimensionality=THREE_O, · type=OEFORMABLE_BODV) . Both THREE_D and DEFORMABLE_BODY are symbolic constants defmed in the abaqusConstants module.

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The default model 1n Abaqus is always naf!led 'Model- I ', which is why when you open a new file you always see 'Model-1' in the model database tr ee on the left in the GUI.

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mdb.models.changeKey(fromName='Model-1', toName='Cantilever Beam') changes the name of the model from the default of 'Model-}' to 'C antilever Beam'. c_hangeKeyO is a method of models which is in the model database, hence we refer to it usihg mdb.models.changeKeyO.

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the models repository is a subclass of a dictionary object which keeps track of model objects. As explained before, a subclass means that it has the same properties and methods of the dictionary object along with a few more properties and methods, such as cbaogeKeyQ, that developers at SIMULIA decided to add in. The model name 'Model- I' is the key, while the value is a model object. The changeKeyO method which is not native to Python essentially allows us to change the key to 'Cantilever Beam' while referring to the same model object.

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beamModel = mdb.models['Cantilever Beam') assigns our model, to the beamMOdel-variable. This is so that in future we do not have to keep referring to it as mdb.models('Cantilever Beam') but can in stead just call it beamModel. Look at the 'create the part' block and notice the statement beamProfileSketch = beamModel .ConstrainedSketch(name= 'Beam CS Profile', sheetSize = S) Don't worry about what it means just yet, I only want to point out that if we did not define the variable beamModel, then the same statement would have to be written as: beamProfileSketch = mdb.models(ccantilever Beam']. ConstrainedSketch (name='Beam CS Profile, sheetSize = S)

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import sketch import part

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Note that the statement can be written without the words 'name' and 'sheetSize' as: beamProfileSketch = beamModel.ConstrainedSketch('Beam CS Profile', 5)

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The statement beamProfileSketch.rectangle(point1=(8.1,8.1), point2=(8.3J-8.1)) uses the rcctangleO method of the ConstrainedSketcb object to draw a rectangle on the sketch plane. The two parameters are the coordinates of the top left and bottom right corners of the rectangle.

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import material This statement imports the material module into the script providing access to objects and methods related to materials.

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The Material object is assigned to the variable beamMaterial.

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beamMaterial.Density{table={(7872, ), )) This statement creates a Density object which specifies the density of the material by using the DensityO method. The Density object is defined in the material module, hence you do not use an 'import density' statement

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Why a table? Well you might have a density that depends on temperature. In which case you would have a table in the form ((de nsity/ , temperature]), (density2,temperature2), (density3,temperature3)) and so on ...

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A Region object is a type of object on which .you can apply an attribute.

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lYou can use a Region object to define the geometry for a section assignment, or a load, or a boundary condition, or a mesh, basically it forms a link between the geometry and the applied attribute. A Region object can be a sequence of Cell objects. In fact it can be a sequence of quite a few other objects, including Node objects, Vertex objects, Edge objects and Face objects. In our script we are assigning a Cell object to it. But si.nce it needs to be a sequence of Cell objects, not just one Cell object that we are providing, we stick the comma at the end to make it a sequence

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This statement assigns _ th~ rootAssembly . to - the variable beam.Assembly. The rootAssembly is an Assembly object. 1t is a member of the Model object. However you do not need to create it using any method, it is created by default when the Model object is created.

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The FieldOutputRequest object is defined in the step module hence you do not use an import fieldOutputRequest statement.

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Tbe Basics of Scripting- Cantilever Beam Example beamModel.HistoryOutputRequest(name='Default History Outputs', createStepName='Apply Load', variables•PRESELECT) This statement . creates a new HistoryOutputRequest object using the HistoryOutputRequest method. The first argument is the name of the object, which is its key in the historyOutputRequests repository.

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#incremental-reading
Incremental reading is a learning technique that makes it possible to read thousands of articles at the same time

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SuperMemo: Incremental reading
swers 3.4 Skill 4: Repetition and review 3.5 Skill 5: Handling large volumes of knowledge 4 Summary 5 Pictures 6 Optional: History of incremental reading 7 See also What is incremental reading? <span>Incremental reading is a learning technique that makes it possible to read thousands of articles at the same time without getting lost. Incremental reading begins with importing articles from electronic sources, e.g. the Internet. The student then extracts the most important fragments of individual




For, the record, the point should riot be shared by more than one face because then the method will return whichever face it first encounters and there is no way of knowing which one it will be.

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When the face we pass as a parameter is set equal to sidelFaces which is the name argument, the normal of the region is the same as the normal of the face. Jf instead we had written side2Faces=top_face, the normal to our region would have pointed into the beam rather than out of it.

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#ISAN3010 #module2
One of the reasons why companies struggle with the application of roadmapping is that there are many specific forms of roadmaps, which often have to be tailored to the specific needs of the firm and its business context.

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#ISAN3010 #module2
Identifying disruptive technologies and surviving in disruptive markets is not easy but roadmaps can help

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#ISAN3010 #module2
A key benefit of roadmapping is the sharing of knowledge and the development of a common vision of where the company is going, and this only comes about by sharing knowledge and making connections

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#ISAN3010 #module2
Sectoral or multiorganization roadmapping promotes knowledge sharing and facilitates the development of a collective vision that can lead to action and collaboration

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The books are on the table.

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How to Use On with Example Sentences
ting something is being supported by something; indicating that something is in a certain situation or location; at a certain time Listen to all | All sentences (with pause) Example sentences: "<span>The books are on the table. " "I want to hang a shelf on the wall. " "I left my keys on the counter. " "I have a stain on my shirt. " "We live on a farm. " "My house is on the left side of the street. " "My dad wa




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The books are on the table.

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How to Use On with Example Sentences
ting something is being supported by something; indicating that something is in a certain situation or location; at a certain time Listen to all | All sentences (with pause) Example sentences: "<span>The books are on the table. " "I want to hang a shelf on the wall. " "I left my keys on the counter. " "I have a stain on my shirt. " "We live on a farm. " "My house is on the left side of the street. " "My dad wa







I want to hang a shelf on the wall.

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How to Use On with Example Sentences
ed by something; indicating that something is in a certain situation or location; at a certain time Listen to all | All sentences (with pause) Example sentences: "The books are on the table. " "<span>I want to hang a shelf on the wall. " "I left my keys on the counter. " "I have a stain on my shirt. " "We live on a farm. " "My house is on the left side of the street. " "My dad was on TV. " "The house is on fire! " "We




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How to Use On with Example Sentences
ed by something; indicating that something is in a certain situation or location; at a certain time Listen to all | All sentences (with pause) Example sentences: "The books are on the table. " "<span>I want to hang a shelf on the wall. " "I left my keys on the counter. " "I have a stain on my shirt. " "We live on a farm. " "My house is on the left side of the street. " "My dad was on TV. " "The house is on fire! " "We







I left my keys on the counter.

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How to Use On with Example Sentences
ing is in a certain situation or location; at a certain time Listen to all | All sentences (with pause) Example sentences: "The books are on the table. " "I want to hang a shelf on the wall. " "<span>I left my keys on the counter. " "I have a stain on my shirt. " "We live on a farm. " "My house is on the left side of the street. " "My dad was on TV. " "The house is on fire! " "We are going on vacation. " "The app




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How to Use On with Example Sentences
ing is in a certain situation or location; at a certain time Listen to all | All sentences (with pause) Example sentences: "The books are on the table. " "I want to hang a shelf on the wall. " "<span>I left my keys on the counter. " "I have a stain on my shirt. " "We live on a farm. " "My house is on the left side of the street. " "My dad was on TV. " "The house is on fire! " "We are going on vacation. " "The app







#ISAN3010 #module2
A strong analytics strategy relates business goals and use cases with how analytics will support employees and the business

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#ISAN3010 #book
Analytics (or data analytics ) can be defined as the systematic quantitative analysis of data or statistics to obtain meaningful information for better decision-making

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#ISAN3010 #book
analysis to understand the status quo that may reflect the result of their efforts to achieve certain objectives.

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#ISAN3010 #book
analytics to identify specific trends or patterns in the data under analysis so that they can predict or forecast the future outcomes or behaviors based on the past trends

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#ISAN3010 #book
hesitation is related to lack of training in the analytical tools, technologies, and processes

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#ISAN3010 #book
the analytics paradigm to break down the processes and systems in complex projects to predict their behavior and outcomes

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#ISAN3010 #book
Assessing feasibility

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#ISAN3010 #book
Managing data overload

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#ISAN3010 #book
Enhancing data visibility and control via focused dashboards

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#ISAN3010 #book
Analyzing project portfolios for project selection and prioritization: Project portfolio analysis is a useful application of analytics

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#ISAN3010 #book
project’s feasibility based on the organization’s project selection criteria, which might include, but not be limited to, the following factors: ■ Technical, economic, legal, political, capacity, and capability constraints ■ Cost-benefits analysis resulting in scoring based on various financial models such as: ■ Net present value (NPV) 1 ■ Return on investment (ROI) 2 ■ Payback period 3 ■ Breakeven analysis 4 ■ Resource requirements ■ Internal resources (only functional department resources, cross-functional resources, cross-organizational resources, or any combination of the preceding) ■ External resources ■ Both internal and external resources ■ Project complexity ■ Project risks ■ Training requirements

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#ISAN3010 #book
select the best course of action based on careful evaluation of various alternatives by analyzing the underlying tangible and intangible criteria is the only way a project manager can lead the project to achieve the stipulated objectives

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#ISAN3010 #book
Decision-making depends on multiple factors including knowledge, skills, tangibles, intangibles, pragmatism, and decision-making methodology

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#ISAN3010 #book
Time Is of the Essence Right and rational decisions made by a project manager in a timely 1 manner are critical for the progress of a project.

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#ISAN3010 #book
Lead by Example Leading by example is an important and effective skill of a project manager to motivate the project team.

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#ISAN3010 #book
Establish Credibility The ability of a project manager to be decisive and make things happen on the project helps her establish her credibility among the project team members as a strong leader

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#ISAN3010 #book
ptg16381985 30 Project Management Analytics Resolve Conflicts and Other Project Problems Projects typically have to deal with lots of uncertainty and involve multiple diverse stake- holders. They involve a variety of conflicts and project problems. The project manager’s responsibility ultimately is to handle and resolve those conflicts and problems effectively to keep the project on track to success.

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#ISAN3010 #book
Avoid Analysis Paralysis

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#ISAN3010 #book
ptg16381985 32 Project Management Analytics 7 Steps to Data-Driven Decision Making Step 5: Propose Potential Possible Solutions (Alternatives) Interpret data analysis results from Step 4 and propose potential possible solutions (alternatives); Define proper metrics. Step 6: Model analytics approach and analyze the proposed alternatives Use appropriate analytics such as predictive analytics, prescriptive analytics, or analytic hierarchy process to analyze proposed alternatives and to select the best alternative. Step 7: Make Decision Make smart informed decision by selecting the best alternative from all potential solution candidates (alternatives) based on the alternative analysis results from Step 6. Step 4: Analyze Data Analyze the collected data to find specific patterns, trends, outliers, and special causes. Step 3: Collect Data Collect data pertaining to the defined problem or situation. Step 2: Review Historical Records / Lessons Learned Check if the current problem occurred in the past. If yes, how was it resolved? If solution is already available, there is no need to re-invent the wheel. Even if the problem at hand did not occur in the past, find if any similar problems occurred in the past and how they were solved if they did occur. Leverage as much as possible to speed up the decision making process. Step 1: Define/Identify the Problem or Situation Clearly understand the problem - Wrong diagnosis means wrong treatment. Figure 2.2 Seven Steps to Data-Driven Decision-Making

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#ISAN3010 #book
Magnitude and complexity of the data: The higher the magnitude and complex- ity of the data, the more difficult and time consuming is the security, storage, and processing of the data

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#ISAN3010 #book
Sources of the data: Sources of data determine the type of data collected. Incor- rect sources means incorrect data and hence incorrect decisions, as discussed in the next section, “Garbage In, Garbage Out.

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#ISAN3010 #book
Quality of the data: Uniform data (attributes) pertaining to various alternatives must be compared to mimic apple-to-apple comparison for fair alternative analy- sis. Also, the quality of the data collected must be adequate to bring forth the true value of a given alternative

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#ISAN3010 #book
Personnel analytical skills: Inadequate analytical skills of data analyst personnel will certainly pose a challenge in ensuring the accuracy, quality, and efficiency of the analysis

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#ISAN3010 #book
Tools and technologies: The speed, accuracy, and quality of data collection, stor- age, analysis, and interpretation processes depend on the available tools and tech- nologies, particularly when the data in question is large and complex

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#ISAN3010 #book
Shelf-life of the data: Data collected that is not processed in a timely manner may become stale and no longer useful

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#ISAN3010 #book
six questions that should be asked to collect the good type and quality of data: ■ What was the source of your data? ■ How well do the sample data represent the population? ■ Does your data distribution include outliers? How did they affect the results? ■ What assumptions are behind your analysis? Might certain conditions render your assumptions and your model invalid? ■ Why did you decide on that particular analytical approach? What alternatives did you consider? ■ How likely is it that the independent variables are actually causing the changes in the dependent variable? Might other analyses establish causality more clearly?

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#ISAN3010 #book
seven Cs of stakeholder management: 1. Concern 2. Communicate 3. Contribute 4. Connect 5. Compound 6. Co-Create 7. Complete

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#ISAN3010 #book
Improve project stakeholder management: Analytics can help improve project stake- holder management by enabling a project manager to predict stakeholder responses to various project decisions. Project stakeholder management is both art and science—art because it depends partly on the individual skillset, approach, and personality of the individual project manager, and science because it is a highly data-driven process

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#ISAN3010 #book
Predict project schedule delays and cost overruns: Analytics can tell a project manager whether the project is on schedule and whether it’s under or over budget. Also, analytics can enable a project manager to predict the impact of various completion dates on the bottom line (project cost).

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#ISAN3010 #book
Project risk identification, rank- ing, and prioritization depend upon multiple factors, including at least the following: ■ Size and complexity of the project ■ Organization’s risk tolerance ■ Risk probability, impact, and horizon ■ Competency of the project or risk manager

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#ISAN3010 #book
Improvement projects typically involve four steps: 1. Understand the current situation. 2. Determine the desired (target) future situation. 3. Perform gap analysis (find the delta between the target and the current situations). 4. Make improvement decisions to address the gap.

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#ISAN3010 #book
Statistical approach comes in handy when dealing with project uncertainties because it includes tools and techniques that managers can deploy to interpret specific patterns in the data pertaining to the project management processes to predict the future more accurately.

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#ISAN3010 #book
Quantitative measure of a process, when that process is performed over and over, is likely to follow a certain frequency pattern of occurrence. In other words, there is a likelihood or probability of recurrence of the same quantitative measure in the long run. This likelihood or probability represents the uncertainty of recurrence of a certain quantitative value of the process.

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#ISAN3010 #book
Normal distribution is the result of the process of accumulation. Usually, the sum or average of the outcomes of various uncertainties constitutes an outcome whose prob- ability distribution is a normal distribution

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#ISAN3010 #book
Poisson Distribution This distribution can be used to count the number of successes or opportunities as a result of multiple tries within a certain time period

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#ISAN3010 #book
Uniform distribution arbitrarily determines a two-point estimate of the highest and low- est values (endpoints of a range) of a random variable. This simplest estimation method allows project managers to transform subjective data into probability distributions for better decision-making especially in risk management

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#ISAN3010 #book
A triangular distribution is called so because of its triangular shape. It is based on three underlying values: a (minimum value), b (maximum value), and c (peak value) and can be used estimate the minimum, maximum, and most likely values of the outcome. It is also called three-point estimation, which is ideal to estimate the cost and duration associ- ated with the project activities more accurately by considering the optimistic, pessimistic, and realistic values of the random variable (cost or duration)

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#ISAN3010 #book
DMAIC stands for the following stages of the Lean Six Sigma life cycle: D efine M easure A nalyze I mprove C ontrol

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#ISAN3010 #book
PDSA cycle follow (refer to Chapter 7 for detailed discussion on the PDSA cycle): ■ Plan: The development of the plan to carry out the cycle ■ Do: The execution of the plan and documentation of the observations ■ Study: The analysis of the observed and collected data during the execution of the PDSA plan ■ Act: The next steps based on the analysis results obtained during study

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#ISAN3010 #book
The AHP approach is a 360 o approach, which includes both subjective and objective criteria in decision-making. The key characteristic of this approach is that it uses pairwise comparisons 16 of all the possible factors of the complex problem at hand and evaluates their relative importance to the decision-making process.

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