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Python for Industrial Engineers

Creating Quality Control Charts using Python libraries

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Quality Control Charts

Quality control charts represent a great tool for engineers to monitor if a process is under statistical control. They help visualize variation, find and correct problems when they occur, predict expected ranges of outcomes and analyze patterns of process variation from special or common causes. Quality control charts are often used in Lean Six Sigma projects and DMAIC projects under the control phase and are considered as one of the seven basic quality tools for process improvement.

The appropriate control chart to use is determined by the type of data (i.e. measurement), the number of defects and the sample size…

Python for Industrial Engineers

Measuring Process Performance

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Process Capability Analysis

Process capability analysis represents a significant component of the Measure phase from the DMAIC (Define, Measure, Analysis, Improve, Control) cycle during a Six Sigma project. This analysis measures how a process performance fits the customer’s requirements, which are translated into specification limits for the interesting characteristics of the product to be manufactured or produced. The results from this analysis may help industrial engineers identify variation within a process and develop further action plans that lead to better yield, lower variation, and fewer defects.


Specifications are the voice of the customer. Every process should be capable of fulfilling the customer’s requirements…


Choosing the Right Types of Simulation For Your Project

Before starting to build any simulation model for a given project, it becomes crucial to identify the types of simulation that best matches the system to be modeled.

Will the system evolve over time?

Will the system agents interact with each other’s and with their environment?

Will agents be capable of adapting to new conditions, thus changing their decision patterns? Is the system to be modeled it a dynamic or complex system?

In this blog, we will review the most popular types of simulation widely used by professionals and academics to conduct simulation studies.

Discrete Event Simulation (DES)


Analyzing Candidates Cover Letter for Jobs Openings

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Writing a strong cover letter is not a trivial task. It could either boost your application and make you more interesting for recruiters and hiring managers or disqualify you from the process. People spend a significant amount of time writing and formatting the perfect cover letter hoping it to be read by a talent acquisition professional and, eventually, help them land a job interview. Unfortunately, not all cover letters are actually ever seen by a human eye.

Due to the high number of applicants and resumes with cover letters submissions to job postings, manual resumes screening processes become tedious, ineffective…


Quality Tools with Python

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Pareto Chart

The Pareto chart, also known as the Pareto distribution diagram, is a vertical bar graph in which values are plotted in decreasing order of relative frequency from left to right. It represents an extremely useful tool during the first stages of analyzing a problem since it helps visualize what problems need attention first by looking at the tallest bars of the chart, which represent the variables with the greatest cumulative effect on a given system.

Developed by the Italian engineer Vilfredo Pareto, the chart provides a graphic representation of the Pareto principle, a theory maintaining that 80% of the output…

Python for Industrial Engineers

Interpreting Quality Control Charts

Image by Isaac Smith available at Unsplash

Quality Control Charts

Quality control charts represent a great tool for engineers to monitor if a process is under statistical control. They help visualize variation, find and correct problems when they occur, predict expected ranges of outcomes and analyze patterns of process variation from special or common causes.

Special causes of variation are detected on control charts by noticing certain types of patterns present on them. In order to truly seize the benefits of control charts, such patterns — and what they represent on a given process — must be recognized to find the reason behind special causes of variation. …

Simulation Modeling

Keys for Succeeding as a Simulation Modeler

Simulation Modeling

Simulation modeling is the process of replicating an existing (or potential) system into a simulation model using software and technology. Simulation models represent great resources for testing multiple systems hypothetical scenarios in risk-free environments while being able to manipulate their parameters, constraints and logic without having to incur in high costs.

However, even with the use of cutting-edge technologies and software, replicating a system into a simulation model represents a challenging task. …

Python for Industrial Engineers

Total Productive Maintenance

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Reliability is the probability that an item, product, machine or equipment will perform a required function for a given period of time, under certain operating conditions. In other words, it is the probability of a non-failure over time.

Simulation Modeling

Steps to make the best out of your simulation study

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Simulation Modeling

Simulation is one of the most widely used operations research and management science techniques. It consists in the use of mathematical methods and computer techniques to imitate or simulate the operations of various kinds of real-world facilities and process, referred as systems. The assumptions of how a system works usually take the form of mathematical or logical relationships; they constitute a model that is used to try to gain understanding on how the corresponding system behaves.

Since most real-world systems are too complex to allow realistic models to be evaluated analytically, these models must be studied by means of simulation…

R for Engineers and Managers

Creating Data Trees using R packages

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Data Trees

Data tress are visual representations of hierarchical data. They are widely used in multiple fields such as decision theory, machine learning, finance, organizational management, routing algorithms, computer science and programming. Data trees help organizing data into groups and subgroups based on a hierarchy.

Data Trees Elements

  • Root node: represents the very top node of the tree. All the existing data points, groups and subgroups end up linked to it. It is the node with the highest hierarchy.
  • Leaves: represent children of nodes with higher hierarchies (i.e. parent nodes). They can also be parent nodes of multiple branches of leaves with lower hierarchies.
  • Attributes

Roberto Salazar

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