Interventions required to meet business objectives from Forecasting Methods,
Quantitative & Qualitative Methods,
Forecast Accuracy , Error Reduction to
CPFR
Interventions required to meet business objectives from Forecasting Methods,
Quantitative & Qualitative Methods,
Forecast Accuracy , Error Reduction to
CPFR
Interventions required to meet business objectives - from Forecasting Methods,
Forecast Accuracy / Error Reduction,
Integrate – Sales Forecast / Production to undertaking a CPFR
This topic is related to Material requirement planning, MRP.
Types of material requirement planning
Benefits of MRP. Limitation of MRP, Objective of MRP, MRP Input, MRP Output, Steps of MRP
Increasingly powerful computer processors, ubiquitous sensors, artificial intelligence, and Massive Data™ will advance the field of forecasting. Yet the job of strategic analyst will remain one of knowing how to present such insights to decision makers.
For more check out https://www.competitivefutures.com and http://www.ericgarland.co
Interventions required to meet business objectives - from Forecasting Methods,
Forecast Accuracy / Error Reduction,
Integrate – Sales Forecast / Production to undertaking a CPFR
This topic is related to Material requirement planning, MRP.
Types of material requirement planning
Benefits of MRP. Limitation of MRP, Objective of MRP, MRP Input, MRP Output, Steps of MRP
Increasingly powerful computer processors, ubiquitous sensors, artificial intelligence, and Massive Data™ will advance the field of forecasting. Yet the job of strategic analyst will remain one of knowing how to present such insights to decision makers.
For more check out https://www.competitivefutures.com and http://www.ericgarland.co
In this presentation, we will discuss production planning system, factors determining production control procedure, role of production planning and control in operations management, scope of production planning and control, its phases and principles. We will also talk about framework for strategy formulations and task control, PPC limitations, effectiveness, PPC in different systems, requirement of an effective PPC in a system and make or buy analysis.
To know more about Welingkar School’s Distance Learning Program and courses offered, visit: http://www.welingkaronline.org/distance-learning/online-mba.html
An immersive workshop at General Assembly, SF. I typically teach this workshop at General Assembly, San Francisco. To see a list of my upcoming classes, visit https://generalassemb.ly/instructors/seth-familian/4813
I also teach this workshop as a private lunch-and-learn or half-day immersive session for corporate clients. To learn more about pricing and availability, please contact me at http://familian1.com
NUMERICAL SIMULATIONS OF HEAT AND MASS TRANSFER IN CONDENSING HEAT EXCHANGERS...ssuser7dcef0
Power plants release a large amount of water vapor into the
atmosphere through the stack. The flue gas can be a potential
source for obtaining much needed cooling water for a power
plant. If a power plant could recover and reuse a portion of this
moisture, it could reduce its total cooling water intake
requirement. One of the most practical way to recover water
from flue gas is to use a condensing heat exchanger. The power
plant could also recover latent heat due to condensation as well
as sensible heat due to lowering the flue gas exit temperature.
Additionally, harmful acids released from the stack can be
reduced in a condensing heat exchanger by acid condensation. reduced in a condensing heat exchanger by acid condensation.
Condensation of vapors in flue gas is a complicated
phenomenon since heat and mass transfer of water vapor and
various acids simultaneously occur in the presence of noncondensable
gases such as nitrogen and oxygen. Design of a
condenser depends on the knowledge and understanding of the
heat and mass transfer processes. A computer program for
numerical simulations of water (H2O) and sulfuric acid (H2SO4)
condensation in a flue gas condensing heat exchanger was
developed using MATLAB. Governing equations based on
mass and energy balances for the system were derived to
predict variables such as flue gas exit temperature, cooling
water outlet temperature, mole fraction and condensation rates
of water and sulfuric acid vapors. The equations were solved
using an iterative solution technique with calculations of heat
and mass transfer coefficients and physical properties.
Welcome to WIPAC Monthly the magazine brought to you by the LinkedIn Group Water Industry Process Automation & Control.
In this month's edition, along with this month's industry news to celebrate the 13 years since the group was created we have articles including
A case study of the used of Advanced Process Control at the Wastewater Treatment works at Lleida in Spain
A look back on an article on smart wastewater networks in order to see how the industry has measured up in the interim around the adoption of Digital Transformation in the Water Industry.
NO1 Uk best vashikaran specialist in delhi vashikaran baba near me online vas...Amil Baba Dawood bangali
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Using recycled concrete aggregates (RCA) for pavements is crucial to achieving sustainability. Implementing RCA for new pavement can minimize carbon footprint, conserve natural resources, reduce harmful emissions, and lower life cycle costs. Compared to natural aggregate (NA), RCA pavement has fewer comprehensive studies and sustainability assessments.
About
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
Technical Specifications
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
Key Features
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface
• Compatible with MAFI CCR system
• Copatiable with IDM8000 CCR
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
Application
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
Final project report on grocery store management system..pdfKamal Acharya
In today’s fast-changing business environment, it’s extremely important to be able to respond to client needs in the most effective and timely manner. If your customers wish to see your business online and have instant access to your products or services.
Online Grocery Store is an e-commerce website, which retails various grocery products. This project allows viewing various products available enables registered users to purchase desired products instantly using Paytm, UPI payment processor (Instant Pay) and also can place order by using Cash on Delivery (Pay Later) option. This project provides an easy access to Administrators and Managers to view orders placed using Pay Later and Instant Pay options.
In order to develop an e-commerce website, a number of Technologies must be studied and understood. These include multi-tiered architecture, server and client-side scripting techniques, implementation technologies, programming language (such as PHP, HTML, CSS, JavaScript) and MySQL relational databases. This is a project with the objective to develop a basic website where a consumer is provided with a shopping cart website and also to know about the technologies used to develop such a website.
This document will discuss each of the underlying technologies to create and implement an e- commerce website.
HEAP SORT ILLUSTRATED WITH HEAPIFY, BUILD HEAP FOR DYNAMIC ARRAYS.
Heap sort is a comparison-based sorting technique based on Binary Heap data structure. It is similar to the selection sort where we first find the minimum element and place the minimum element at the beginning. Repeat the same process for the remaining elements.
Cosmetic shop management system project report.pdfKamal Acharya
Buying new cosmetic products is difficult. It can even be scary for those who have sensitive skin and are prone to skin trouble. The information needed to alleviate this problem is on the back of each product, but it's thought to interpret those ingredient lists unless you have a background in chemistry.
Instead of buying and hoping for the best, we can use data science to help us predict which products may be good fits for us. It includes various function programs to do the above mentioned tasks.
Data file handling has been effectively used in the program.
The automated cosmetic shop management system should deal with the automation of general workflow and administration process of the shop. The main processes of the system focus on customer's request where the system is able to search the most appropriate products and deliver it to the customers. It should help the employees to quickly identify the list of cosmetic product that have reached the minimum quantity and also keep a track of expired date for each cosmetic product. It should help the employees to find the rack number in which the product is placed.It is also Faster and more efficient way.
Sachpazis:Terzaghi Bearing Capacity Estimation in simple terms with Calculati...Dr.Costas Sachpazis
Terzaghi's soil bearing capacity theory, developed by Karl Terzaghi, is a fundamental principle in geotechnical engineering used to determine the bearing capacity of shallow foundations. This theory provides a method to calculate the ultimate bearing capacity of soil, which is the maximum load per unit area that the soil can support without undergoing shear failure. The Calculation HTML Code included.
2.
Forecasting is a process of estimating a future event
by casting forward past data.
The past data are systematically combined in a
predetermined way to obtain the estimate of the
future.
In business applications, forecasting serves as a
starting point of major decisions in finance,
marketing, productions, and purchasing.
Forecasting
3.
Objective
To predict demand for planning purposes
Laws of Forecasting
Forecasts are always wrong.
Forecasts always change.
The further into the future, the less reliable the forecast will be.
5. Determine the purpose of the forecast. How will it be used
and when will it be needed?
Establish a time horizon. The forecast must indicate a time
interval, keeping in mind that accuracy decreases as the time
horizon increases.
Obtain, clean, and analyse appropriate data. Obtaining the
data can involve significant effort. Once obtained, the data may
need to be “cleaned” to get rid of outliers and obviously
incorrect data before analysis.
Select a forecasting technique.
Make the forecast.
Monitor the forecast. A forecast has to be monitored to
determine whether it is performing in a satisfactory manner.
Steps of Forecasting
8.
Quantitative Models are classified into two models
1) Time Series Models
A time series is an uninterrupted set of data
observations that have been ordered in equally spaced
intervals (units of time).
2) Associated Models
Associative (causal) forecasting is based on
identification of variables (factors) that can predict
values of the variable in question
Quantitative Methods
9. A time series is a time-ordered sequence of observations
taken at regular intervals.
Forecasting techniques based on time-series data are made on
the assumption that future values of the series can be
estimated from past values.
Analysis of time-series can often be accomplished by merely
plotting the data and visually examining the behaviour of the
series.
One or more patterns might appear: trends, seasonal
variations, cycles, or variations around an average. In
addition, there will be random and perhaps irregular
variations.
Time Series Analysis
Technique
10.
These behaviours can be described as follows:
Trend refers to a long-term upward or downward movement in the data.
Population shifts, changing incomes, and cultural changes often account for
such movements.
Seasonality refers to short-term, fairly regular variations generally related to
factors such as the calendar or time of day.
Cycles are wavelike variations of more than one year’s duration. These are
often related to a variety of economic, political, and even agricultural
conditions.
Irregular variations are due to unusual circumstances such as severe
weather conditions, strikes, or a major change in a product or service.
Whenever possible, these should be identified and removed from the data.
Random variations are residual variations that remain after all other
behaviour's have been accounted for.
11. A trend line fitted to historical data points can project into the
medium to long-range
Linear trends can be found using the least squares technique
y = a + bx
Where,
y= computed value of the variable to be predicted (dependent
variable)
a= y-axis intercept
b= slope of the regression line
x= the independent variable
Estimated by least squares method
Linear Regression
12.
Criteria of finding a and b:
Equation: ii bxaY ˆ
Slope: 22
1
1
xnx
yxnyx
b
i
n
i
ii
n
i
Y-Intercept: xbya
13. MA is a series of arithmetic means
Used if little or no trend, seasonal, and
cyclical patterns
Used often for smoothing
Provides overall impression of data over
time
Equation,
Simple Moving Average
Method
MA
n
n
Demand in Previous Periods
14.
A manager of a museum store that sells historical replicas. He
want to forecast sales of item (123) for 2000 using a 3-period
moving average.
1995 4
1996 6
1997 5
1998 3
1999 7
Time Response
Yi
Moving
Total
(n=3)
Moving
Average
(n=3)
1995 4 NA NA
1996 6 NA NA
1997 5 NA NA
1998 3 4+6+5=15 15/3=5.0
1999 7 6+5+3=14 14/3=4.7
2000 NA 5+3+7=15 15/3=5.0
16.
Used when trend is present
Older data usually less important
Weights based on intuition
Often lay between 0 & 1, & sum to 1.0
Equation
Weighted moving
average method
WMA =
Σ(Weight for period n) (Demand in period n)
ΣWeights
17.
Increasing n makes forecast less sensitive to changes
Do not forecast trend well due to the delay between
actual outcome and forecast.
Difficult to trace seasonal and cyclical patterns.
Require much historical data.
Weighted MA may perform better.
Disadvantages of Moving
Average Methods
18.
Form of weighted moving average
Weights decline exponentially
Most recent data weighted most
This method requires only the current demand and forecast
demand.
This method assigns weight to all the previous data.
The reason this is called exponential smoothing is that
each increment in the past is decreased by (1-α).
Exponential Smoothing
Method
19.
Ft = Ft-1 + (At-1 - Ft-1)
= At-1 + (1 - ) Ft-1
Ft = Forecast value
At = Actual value
= Smoothing constant
20.
Suppose you are organizing a Kwanza meeting. You want to
forecast attendance for 2000 using exponential smoothing
( = .10). The 1995 (made in 1994) forecast was 175.
Actual data:
1995 180
1996 168
1997 159
1998 175
1999 190
23.
Why Causal Forecasting ?
There is no logical link between the demand in the
future and what has happened in the past
There are other factors which can be logically linked to
the demand
Example 1: There is a strong cause and effect
relationship between future demand for doors and
windows and the number of construction permits
issued at present.
Example 2: The demand for new house or automobile is
very much affected by the interest rates changed by
banks.
Casual method