The true Willets Point is the site of Fort Totten near Baysidebut over the course of the 20th century it became commonplace to apply the name "Willets Point" derived from the street, rather than the geographical feature to this area instead. Since then, several redevelopment plans for Willets Point were proposed, but never implemented.
Economics Lean Six Sigma Six Sigma is a quality improvement methodology focused on reducing product or service failure rates to a level of perfection.
Structured, data driven approaches are used to eliminate the number of defects across all business areas, such as management, supply chain, design, manufacturing, and customer satisfaction.
The overall goal is to produce better products and services more efficiently and effectively, while reducing costs. The DMAIC process will assist in defining the problem and scope of the project and ensure that these objectives are accounted for throughout the study.
The concept of Lean centers on the continuous elimination of waste in processes, thereby increasing customer satisfaction while reducing the total costs required to produce the same goods or services.
Common qualitative forecasting methods include expert opinion, sales force polling, the Delphi Method, and customer surveys. Quantitative Forecasting — The historical pattern of the data, i. Inventory Theory — Scientific inventory management is used to assist companies to determine how much of a product should be ordered, or produced, and when the order should be placed so the total inventory costs are minimized.
Aggregate Production Planning — Consists of efforts to plan a desired output over a longer range by adjusting the production rate, employment, inventory, and other controllable variables.
Common pure strategies include varying workforce size to fulfill demand by employment only, to maintain a stable workforce but permit overtime, maintain a stable workforce but carry inventory, implement a backorder strategy, or implement a subcontracting strategy.
Material Requirements Planning MRP — Uses the Master Production Schedule MPS to create schedules that identify parts and subcomponents needed to produce an end product, the quantity of the parts and subcomponents needed, and the dates when the materials need to be ordered.
Just-In-Time JIT — A pull system with the goal of reducing the work-in-process to a minimum by only moving items when requested by a higher level in the production process. Production Planning and Scheduling — Project management is a strategic component that involves planning, organizing, staffing, controlling, and monitoring a project in an efficient and effective manner, thus relating the project results to a business objective.
Job Sequencing and Operations Scheduling — Job sequencing focuses on determining the schedule for machine process jobs such that a specific measure of performance, e.
Assembly Line Balancing ALB analyzes assembly operations such that workstations are assigned in an order to achieve equal balance between stations and increase the overall efficiency and effectiveness of the assembly line.
Markov Chain Analysis — A descriptive technique that provides probabilistic information about a decision situation.
Analyzes systems that exhibit probabilistic movement from one state, or condition, to another over time. Queueing Theory — A descriptive modeling technique that describes a solution to allow for analysis of concepts such as the expected number of entities, e.
Optimization Linear Programming — An optimization problem for which the goal is to maximize, or minimize, a linear objective function with respect to a set of linear constraints.
Linear programming is used throughout several industries typically with the primary goal of maximizing a profit function or minimizing a cost function. Common linear programming applications include work-scheduling, budgeting, financial planning, transportation, transshipment, and network models.
Integer Programming — A linear program for which some or all of the variables are required to be non-negative integers. Common integer programming applications include investment decision making, facility location, and machine scheduling problems.
Types of nonlinear programming include quadratic, convex, non-convex, geometric, and fractional programming. Multiple Criteria Decision Making — An optimization problem for which several conflicting criteria are simultaneously optimized. An example of multiple criteria decision making is goal programming, which chooses one of the multiple criteria as the primary criterion and use it as the objective function to be optimized.
The remaining criteria are assigned acceptable values and treated as constraints. The criteria are treated as targets with the goal of producing a solution as close as possible to the targets based on priorities. Heuristic algorithms are used in many applications, but one common area of application are network analysis models.
Data Analysis and Management Data Collection — Develop comprehensive data collection plans to assure that unbiased and relevant data is collected to answer the questions being asked and stay within scope. Data Analysis — Apply advanced statistical tools, such as hypothesis testing, statistical process control, process capability analysis, analysis of variance, regression analysis, root cause analysis, and design of experiment to appropriately draw conclusions about the available data.
Big Data Mining — Use advanced tools, such as pivot tables, to stratify and analyze large amount of data in an efficient and effective manner.
Very useful in determining what data and information is available and what data may need to be collected in order to answer a question or finish a project. Data Management — Develop user friendly tools that will allow for easy manipulation of data and allow for efficient and effective analysis.
With a few clicks, easily run several courses of action to quantify key parameters, such as cost and performance. Data Reports — Provide thorough reports discussing the project from start-to-finish, including the data collection and analysis processes, as well as all conclusions that resulted.
Will also provide concise executive summaries for upper management personnel to highlight the main findings from the study. Modeling and Simulation Use techniques such as Monte Carlo simulations and stochastic simulations to analyze processes and run multiple scenarios to estimate the expected changes in performance parameters.Re: Calgary Telus Spark Science Museum.
Triangle steel employed 3D modeling for the entire project for the steel installation. This allowed for very easy conflict resolution. Ok, finally! Look what I have for you a quick little tutorial on how to construct the scrappy triangle blocks I used in my Nautical quilt..
A few things before we start this tutorial will show you my method for making a scrappy triangle block. Project management triangle.
Triple constraints. Iron triangle. Every project balances time, money, and scope. You can’t change one without affecting at least one of the others. The project manager’s job is to keep the whole triangle from falling apart. Whenever you kick off a project, walking the team through the Iron Triangle with the client is a highly recommended exercise.
The “triangle” nicely pulls together project constraints and our assumptions about them, and for the agile team that will actually be executing and delivering code, it’s an especially great tool to level-set.
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