Insight diagram
Based on Emery Roe's Nov 2024 Pastoralists presentation slides posted on his mess and reliability blog When Complex is as Simple as it gets..
Reliability Professionals and Critical Infrastructures
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Simulation of MTBF with controls

F(t) = 1 - e ^ -λt 
Where  
• F(t) is the probability of failure  
• λ is the failure rate in 1/time unit (1/h, for example) 
• t is the observed service life (h, for example)

The inverse curve is the trust time
On the right the increase in failures brings its inverse which is loss of trust and move into suspicion and lack of confidence.
This can be seen in strategic social applications with those who put economy before providing the priorities of the basic living infrastructures for all.

This applies to policies and strategic decisions as well as physical equipment.
A) Equipment wears out through friction and preventive maintenance can increase the useful lifetime, 
B) Policies/working practices/guidelines have to be updated to reflect changes in the external environment and eventually be replaced when for instance a population rises too large (constitutional changes are required to keep pace with evolution, e.g. the concepts of the ancient Greeks, 3000 years ago, who based their thoughts on a small population cannot be applied in 2013 except where populations can be contained into productive working communities with balanced profit and loss centers to ensure sustainability)

Early Life
If we follow the slope from the leftmost start to where it begins to flatten out this can be considered the first period. The first period is characterized by a decreasing failure rate. It is what occurs during the “early life” of a population of units. The weaker units fail leaving a population that is more rigorous.

Useful Life
The next period is the flat bottom portion of the graph. It is called the “useful life” period. Failures occur more in a random sequence during this time. It is difficult to predict which failure mode will occur, but the rate of failures is predictable. Notice the constant slope.  

Wearout
The third period begins at the point where the slope begins to increase and extends to the rightmost end of the graph. This is what happens when units become old and begin to fail at an increasing rate. It is called the “wearout” period. 
BATHTUB MEAN TIME BETWEEN FAILURE (MTBF) RISK
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Introduction:
This model aims to show that how the Tasmania government's COVID-19 policy can address the spread of the pandemic and in what way these policies can damage the economy.

Assumption:
Variables such as infection rate, death rate and the recovery rate are influenced by the actual situation.
The government will implement stricter travel bans and social distant policies as there are more cases.
Government policies reduce infection and limit economic growth at the same time.
A greater number of COVID-19 cases has a negative effect on the economy.

Interesting insights:
A higher testing rate will make the infection increase and the infection rate will slightly increase as well. 
Government policies are effective to lower the infection, however, they will damage the local economy. While the higher number of COVID-19 cases also influences economic activities.
Model of COVID-19 outbreak in Burnie_Guoyu Shen
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This is the summary of lecture ​1 of my Course about StartUps. It's an intro to the startup ecosystem and the different stakeholders that can interact with your new enterprise at different stages of its evolution and growth. -version 1 - for info or suggestions: bonato.pietroz@gmail.com
StartUp ecosystem
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Model description: 

This model is designed to simulate the Covid-19 outbreak in Burnie, Tasmania by estimating several factors such as exposed population, infection rate, testing rate, recovery rate, death rate and immunity loss. The model also simulates the measures implemented by the government which will impact on the local infection and economy. 

 

Assumption:

Government policies will reduce the mobility of the population as well as the infection. In addition, economic activities in the tourism and hospitality industry will suffer negative influences from the government measures. However, essential businesses like supermarkets will benefit from the health policies on the contrary.

 

Variables:

Infection rate, recovery rate, death rate, testing rate are the variables to the cases of Covid-19. On the other hand, the number of cases is also a variable to the government policies, which directly influences the number of exposed. 

 

The GDP is dependent on the variables of economic activities. Nonetheless, the government’s lockdown measure has also become the variable to the economic activities. 

 

Interesting insights:

Government policies are effective to curb infection by reducing the number of exposed when the case number is greater than 10. The economy becomes stagnant when the case spikes up but it climbs up again when the number of cases is under control. 

Sample Model of COVID-19 outbreak in Burnie Tasmania by Yim Fong Ng (544885)
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​BACKGROUND:

The following simulation model demonstrates the relationship between supply, demand and pricing within the real estate and housing world. I have based the model on a small city with a population of 100,000 residents as of 2015. 

AXIS:

X-Axis
The X-Axis shows the time. It begins in 2015 in the month of October and continues for 36 consecutive years. 

Y-Axis
There are 2 Y-Axis on this model. The left hand side relates to the price, demand, and supply, while the right hand side solely lists the population.

As you could see, this town has a population of 100,000 residents to-date. The bottom of the model shows a population loop that produces an exponential growth rate of 2.5%. This dynamic and growing city populates approximately 240,000 residents after 36 years.

MODEL

The model consists of 2 folders named: Buyers/Consumers & Suppliers/Producers. This first folder represents the 'Demand'. It includes a buyers growth rate, buyers interest increase and decrease, a price demand and the demand price. The formulas form an exponential rise in demand due to the rapid and continuous increase in population in this new city. As population increases, so does the demand from buyers. 

The second folder conveys the supply of houses. It includes a sophisticated loop of real estate. Residents who own houses in the market decide to sell the home. This becomes the Houses for sale, also known as the 'supply'. Those houses are sold and the sold houses re-enter the market and the loop continues. 

The supply has an inverse relationship with the price. When prices drop, supplies drop because the demand goes up. And when the price goes up, so does the supply. This will represent the growth of new houses in the market. 

PRICE

Note: The price is based on monthly rent rates.

The price is dependant on many variables. Most importantly, the supply and demand. It also includes factors such as expectations & the economic value of the house. I have included a stable, 'good' economic value for all homes as this fictional town is in a stable and growing area.

Price fluctuates throughout the entire simulation, however it also goes up in price. Over the years houses continue to rise in price while they regularly fluctuate. For example, in 2018 (3 years later), the max price for a home was: $4254.7 and min price was: $852.98. On the other hand, in October 2051 (36 years later), the max price was: $14906 and the min price was: $7661. (This is based on the following data: Houses for Sale: 500, Houses that have sold: 100, Houses in the Market: 730).

SLIDERS

There are 3 sliders on the bottom that could be altered. The simulation would react accordingly. The 3 sliders include changeable data on:
- Houses for Sale.
- Houses that have Sold.
- Houses in the Market.


Real Estate Simulation Assignment - Mitchell Bassil 43290264
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3. PROBLEMAS e  PERGUNTAS SOBRE  projetos de SISTEMA INTEGRADO DE GESTÃO CUSTOS , INVESTIMENTOS BASEADO MODELOS MATEMÁTICOS: veja  https://docs.google.com/document/d/1oGmItBcErhVF0PWuI37AnpP3n8Up3Zu45W7QB1MMbcY/edit?usp=sharing

Projeto  de investimentos , custos   e viabilidade econômico de LCC

A planta foi dimensionada para produzir 9.000 Ton/ano da Resina usando o matéria prima

LCC , operando 24h/dia, durante os três turnos por 300 dias/anuais. O preço do produto de projeto de lcc 

veja  o prova html aula passados 


1. Calcule o investimento em planta (If) usando o método rápido e investimento em

equipamento (Ie) baseado no método de lang. Admita valor de N e f1 de acordo com o fluxograma do processo.

Dados fornecidos: Entrada (alimentação)-sólido; Saída-líquido;

Equipamentos principais da produção: Destilador e fermentador.

2. Calcule o investimento fixo total pelo método chilton através das estimativas dos investimentos fixos diretos: Tubulação, instrumentação, estrutura física, planta de serviço e conexões entre unidades; e investimentos fixos indiretos. Tome como base o investimento em equipamentos.

             veja dados na prova html   simulados sobre fator chiltons , modelos  de lang , decico , chiltons e dados na prova html 


3. Calcule o custo de mão-de- obra direta e indireta baseando-se no fluxograma de processo , atualizando  o valor salário mínimo e nos salários:

Valor do salário mínimo = R$180,00

Engenheiro químico = 10 salários mínimos

Operador industrial = 3 salários mínimos

Administração:

Gerente = 8 salários mínimos

Auxiliar de escritório = 3 salários mínimos

Secretária = 2 salários mínimos

Dados fornecidos: Considere os encargos sociais de 65% sobre o salário base. Mão-de- obra

indireta seja 20% da mão-de- obra direta. O custo de mão-de- obra indireta engloba

manutenção.

4. Calcule os custos fixos abaixo, baseando-se pelo método Sebrae:

Dados 

4.1 Depreciação = 10%If

4.2 Manutenção = 3%If

4.3 Seguro = 1%If

4.4 Imposto = 2%If

5. Calcule o custo de consumo anual de matéria-prima de acordo com os dados  , veja prova html a seguir 

5.2 Calcule o custo unitário de matéria prima sendo 80% do valor do custo total anual da

matéria-prima. , dados  , veja na link enunciados  e prova html 

6. Calcule os custos totais:

6.1 Encargos anuais

6.2 Administração = 0.6 (mão-de- obra direta + mão-de- obra indireta + encargos anuais)

6.3 Suprimentos = 0.15 (Manutenção)

6.4 Calcule os custos fixos

6.5 Calcule os custos variáveis

6.6 Calcule os custos variáveis

* Os custos fixos englobam administração

Custo variável = custo de matéria – prima + custo de utilitários + custo de suprimentos.

Custo de suprimentos é 10% da mão-de- obra direta.

Depreciação = 10% do investimento fixo.

7. Estimar o ponto de equilíbrio em quantidade e em porcentagem baseado em dados obtidos de custo variável unitário) e Custo fixo do problema 06.


8. Estime os itens da análise de investimento:

– Taxa de retorno de engenharia simples

– Tempo de retorno

– % de lucro em relação ao preço de venda

– Lucro após o imposto de renda

– Lucratividade

– Rentabilidade

– Fluxo de caixa

9. Estimar potencial econômico de projeto de perdas devido ao baixo rendimento de operação em nível de 90% de rendimento máximo em vez de 98%.

 

 Dados de  consumos de  materiais e energia obtidos  via uso de calculadora usando    quiz html de modelos já apresentados aula passos





NOME E DESCRIÇÃO

LINK

TAMANHO

Prova1validacao.:Investimento Fixo e Tomada de Decisões Rápidas

https://canvas.instructure.com/courses/780776/files/folder/provahtml?preview=51184101

33 KB

Prova.2 Validacao .Investimento fixo método Lang

https://canvas.instructure.com/courses/780776/files/folder/provahtml?preview=51184144

32 KB

Prova 3 :Investimento Fixo método Chilton

ihttps://canvas.instructure.com/courses/780776/files/folder/provahtml?preview=51184169


33 KB

Prova4:Custo Fixo

https://canvas.instructure.com/courses/780776/files/folder/provahtml?preview=51184189

32 KB

Prova 5::Custo de mao de obra

customaohtm custo de mao de obra

33 KB

Prova 6 Validao : Custo de mat,comb e enegia

CustoMat prima , energia

34 KB

Prova 7 Custo total

custo de operacional  de  producao

33 KB

Prova 8 Ponto deEquilibrio 

ponto de eqilibrioibrio

32 KB

Prova 9:Analise de lucro e beneficios

Fluxo de caixa

33 KB




gestao economical planta resina fenolicas lcc .Modelos e resultados validados validado via planilhas
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Urbanisation insight
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Overview
The model simulates how logging in with tourism(mountain biking) in Derby Tasmania.
How the model works.
Trees grow, loggers cut them in order to sell them because of demand for Timber.
Mountain cyclist depends on satisfaction and expectation.  Satisfaction and Expectation depends on Scenery number of trees compared to visitor and Adventure number of trees and users.  Park capacity limits the number of users.  Local Business is influenced by the timber and number of Mountain Cyclist. Employment is influenced by the number of mountain cyclist and logging activity.

Simulation of Mountain Cyclist vs logging
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Decarbonization Stories
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An initial study of the economics of single use coffee pods.
Real Coffee Pods ISD Humanities v 1.02
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GSGS_GREECE_GERMANY_MIGRATION_DRAFT
29 2 months ago
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Format: Given pre-conditions when independent variables(s) then dependent variable

Given Earnings Decline (0.25), Spending Variance (55), Initial Investment (500) and Rate of Return (RandNormal(0.06, 0.12)) when one of these independent variables change then how sensitive is Investment (22) over a 30 year time period (-1,000)

H1: if you Earn more then Investment will last much longer => rejected

H2: if you Spend less then Investment will last much longer => accepted

H3: if your Initial Investment is higher then Investment will last much longer => accepted

H4: if you reduce your Spend when Investments are declining then Investment will last much longer => accepted

Given Earnings Decline (0.25), Spending Variance (55), Initial Investment (500) and Rate of Return (RandNormal(0.06, 0.12)) when one of these independent variables are optimised then Investment will last exactly 30 years by minimising the absolute investment gap

H1: if you set an appropriate Spending Base then remaining Investment is 0 => rejected

H2: if you set an appropriate Spending Reduction then remaining Investment is 0 => rejected

Source for investment returns: https://seekingalpha.com/article/3896226-90-year-history-of-capital-market-returns-and-risks
OrangeFortune | Wealth Management when Retiring
4 3 months ago
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Clone of IM-91683 from jacqui and vincy Summary of paper map produced by participants at the compelling case for prevention workshop 6 june 2017. 

Current premier version containing Story Steps and text for vincy to update.
This is clone of 97129 via Vincy.
FINAL Clone of Concept Map produced by CCP Workshop 1
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Farming_small vs large
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there is a distributed net of independent carriers interacting geographically to build continuous supply chain. We model the dynamics of the system, assuming scarcity of available agents, under the condition that the total path must be no longer then X defined economically.
interaction between members of logistic chain
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Current and proposed Structure of CCP and related Models expanding on the details provided in the Project Completion plan IM-101760
Structure of the CCP Models
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OVERSHOOT GROWTH GOES INTO TURBULENT CHAOTIC DESTRUCTION

The existing global capitalistic growth paradigm is totally flawed

The chaotic turbulence is the result of the concept of infinite bigness this has been the destructive influence on all empires and now shown up by Feigenbaum numbers and Dunbar numbers for neural netwoirks

See Guy Lakeman Bubble Theory for more details on keeping systems within finite limited size working capacity containers (villages communities)

OVERSHOOT GROWTH INTO TURBULENCE
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This high-level simulation model presented by Jay Forrester in his book World Dynamics, simulates socio-economic-environmental world system. The world Model was created in a time where pollution and other negative effects of industrialization and economic growth started to become recognized in 1970. For this exam purpose, we have rebuilt the model to do some experiments and analyze the results. 
World Model1
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Economic BPA/BPS Model
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Model based on chapter 10 (opportunity cost) of the book Modeling Dynamic Economic Systems
Opportunity cost II
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ISCI 360 Project - Stage 2

Our model examines the relationship between two straw types (plastic straws and biodegradable straws) and their impact on the environment and economics. Specifically, we are interested in figuring out whether biodegradable straws are a viable solution to plastic straws

Our model is broken down into three aspects: Social, Environmental and Economic. Color coding is used to differentiate between the different aspects and is explained below:
Turquoise represents the social aspect. 
Purple represents the economic aspects.
Green represents the environmental aspects. 
Blue represents other crucial stocks and flows in the model that do not necessarily fit into the three aspects above. 

In our model, the Canadian population is assumed to increase steadily until a carrying capacity is reached. This can be seen in the graph as the line increases linearly before plateauing indefinitely. We assumed that we will be able to maintain the population at our carrying capacity due to technological advances. 

Social Aspect:
The social aspect refers to the impact that awareness of the detrimental costs of straws can have on the usage of straws. The two flows that contribute to awareness are word of mouth (i.e. your friends and family informing you about the effects of straws and influencing you to stop using them) and media coverage (i.e. the media highlights the effects of straws). Both of these flows are dependent on the Canadian population such that 25% of the Canadian population at any time will be impacted by word of mouth or media coverage. (Side note: since word of mouth and media coverage are dependent on the Canadian population, they will plateau when the population does.) This is an arbitrary number but was chosen to show what a change in perspectives of the Canadian population can do. These flows input into an 'awareness of detrimental effects of using plastic straws' stock that reduces the number of plastic straws being used. 

Plastic Straws
According to data from the United States individuals usually use 1.6 straws everyday and thus, we have assumed that to be true in Canada as well. Plastic straws start at a base value (due to the previous straw usage) and grow with the Canadian population while subtracting the awareness component of the model. 

Environmental Aspect 
Since the decomposition of plastic versus paper is significantly different, the amounts that accumulate in the ocean and landfills can be monitored. In addition, the impact on the environment can be monitored. Since plastic straws take longer to decompose, they have a larger impact on wildlife in the ocean than biodegradable straws. Thus, as the plastic straw usage decreases, the amount of habitat loss occurring plateaus. We have also included the aspect of clean-up in which the plastic from the ocean can be moved to the landfill. You will notice that the habitat loss plateaus but does not decrease. This is because we cannot reverse the damage we have done (without additional rigorous clean-up) but can mitigate additional damage. (Please note that clean-up affects only the stock 'Plastic Straws in the ocean' and thus, does not affect the stock 'habitat loss.' Therefore, clean-up will reduce the number of plastic straws in the ocean and indirectly affect the stock 'habitat loss.' However, it will not clean up the plastic straws already impacting 'habitat loss.')

Economic Aspect
The economic aspect monitors the amount of money it takes to make plastic straws versus biodegradable straws and the amount of money the government needs to fund ocean clean-ups. It can be seen that a the usage of plastic straws decreases, the need for clean-up money from the government decreases. However, there is a base level of damage that has already been done by us and thus, larger scale clean-ups will be needed to reverse that. In other words, smaller clean-ups will mitigate the damage we are currently doing but not reverse the damage we have already done. We can also track the cost of making each straw; it can be seen that biodegradable straws are more expensive to make. 

However, the energy required to make the straws is less for biodegradable straws than plastic straws. Thus, there are trade-offs for using biodegradable straws.

Although, biodegradable straws are more expensive, they require less energy to make, decompose faster, require less funding for clean-up and impact the wildlife in the ocean to a lesser degree
Project Stage 2
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Introduction:
This simulation model demonstrates the outbreak of Covid-19 in Burnie, Tasmania and how the corresponding government’s responses affect the spreading of Covid-19. Meanwhile, this model also shows how the economy in Burnie is influenced by the impacts of both Covid-19 and government policies.

Variables: 
This simulation contains some relevant variables as follow:

Variables in Covid-19 outbreaks: (1) Infection rate, (2) Recovery rate, (3) Death rate, (4) Immunity loss rate

Variables in Government policies: (1) Vaccination rate, (2) Lockdown, (3) Travel ban, (4)Quarantine

Variables in Economy: (1) E-commerce business, (2) Unemployment rate, (3) Economic growth rate.

Assumption:
Government responses would be triggered when reported Covid-19 cases are at least 10.

The government policies reduce the spreading of Covid-19, but they would also limit economic development at the same time due to the negative impact of the policies on the economy is greater than the positive impact.

The increase in reported Covid-19 cases would negatively affect economic growth.

Interesting Insights:
The first finding is that the death number would keep increasing even though the infection rate has decreased, but with stronger government policies (such as implementing a coefficient over 25%), no more death numbers will occur caused by Covid-19.

The second finding is that as government policies limit business activities, with the increasing number of reported Covid-19 cases, economic growth will suffer a severe blow even if e-commerce grows, it can’t make up for this economic loss.
BMA 708 assignment 3 - simulation model of Covid-19 Outbreak in Burnie, Tasmania