Edmond  Herzog

Edmond Herzog

1596547800

Root Cause Analysis and Its Impact on Your Bottom-line

Global Quality Compliance leader, Shellye Archambeau says that:

Experts have estimated that COPQ typically amounts to 5–30 percent of gross sales for manufacturing and service companies. Independent studies reveal that COPQ is costing companies millions of dollars each year, and its reduction can transform marginally successful companies into profitable ones. Yet most executives believe their company’s COPQ is less than 5 percent, or just don’t know what it is.

For a company selling to consumers, 5–30% of consumers may be experiencing poor product quality — consider the cost of lost repeat sales. For B2B companies, there is a loss in credibility, cost of personnel almost continuously engaged in root cause analysis, and higher cost of manufacturing.

Most manufacturing organizations will perform statistical process control (SPC) assessment of their operations — more easily for continuous processes. For one, continuous processes have generally had sensors and control systems put in place — making such analysis easier. However, this is not enough. Many manufacturing operations, however, are batch processes; these processes often have few sensors and most data is tracked manually.

There is a large number of processes (whether continuous or batch), where SPC analysis is limited to only certain portions of the process AND the data is not digitally accessible easily. In such processes, the cost of tracking failures and performing root cause analysis is high.

A number of electronics devices are used in applications such as medical applications, critical testing, or defense, where quality is critical. The manufacturing process of many of these include use of polymers as underfill material, and sealant materials. Variability in raw material quality or processing can cause failures that would be critical.

#manufacturing #ai #quality

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Buddha Community

Root Cause Analysis and Its Impact on Your Bottom-line
Ian  Robinson

Ian Robinson

1623856080

Streamline Your Data Analysis With Automated Business Analysis

Have you ever visited a restaurant or movie theatre, only to be asked to participate in a survey? What about providing your email address in exchange for coupons? Do you ever wonder why you get ads for something you just searched for online? It all comes down to data collection and analysis. Indeed, everywhere you look today, there’s some form of data to be collected and analyzed. As you navigate running your business, you’ll need to create a data analytics plan for yourself. Data helps you solve problems , find new customers, and re-assess your marketing strategies. Automated business analysis tools provide key insights into your data. Below are a few of the many valuable benefits of using such a system for your organization’s data analysis needs.

Workflow integration and AI capability

Pinpoint unexpected data changes

Understand customer behavior

Enhance marketing and ROI

#big data #latest news #data analysis #streamline your data analysis #automated business analysis #streamline your data analysis with automated business analysis

Tyrique  Littel

Tyrique Littel

1604008800

Static Code Analysis: What It Is? How to Use It?

Static code analysis refers to the technique of approximating the runtime behavior of a program. In other words, it is the process of predicting the output of a program without actually executing it.

Lately, however, the term “Static Code Analysis” is more commonly used to refer to one of the applications of this technique rather than the technique itself — program comprehension — understanding the program and detecting issues in it (anything from syntax errors to type mismatches, performance hogs likely bugs, security loopholes, etc.). This is the usage we’d be referring to throughout this post.

“The refinement of techniques for the prompt discovery of error serves as well as any other as a hallmark of what we mean by science.”

  • J. Robert Oppenheimer

Outline

We cover a lot of ground in this post. The aim is to build an understanding of static code analysis and to equip you with the basic theory, and the right tools so that you can write analyzers on your own.

We start our journey with laying down the essential parts of the pipeline which a compiler follows to understand what a piece of code does. We learn where to tap points in this pipeline to plug in our analyzers and extract meaningful information. In the latter half, we get our feet wet, and write four such static analyzers, completely from scratch, in Python.

Note that although the ideas here are discussed in light of Python, static code analyzers across all programming languages are carved out along similar lines. We chose Python because of the availability of an easy to use ast module, and wide adoption of the language itself.

How does it all work?

Before a computer can finally “understand” and execute a piece of code, it goes through a series of complicated transformations:

static analysis workflow

As you can see in the diagram (go ahead, zoom it!), the static analyzers feed on the output of these stages. To be able to better understand the static analysis techniques, let’s look at each of these steps in some more detail:

Scanning

The first thing that a compiler does when trying to understand a piece of code is to break it down into smaller chunks, also known as tokens. Tokens are akin to what words are in a language.

A token might consist of either a single character, like (, or literals (like integers, strings, e.g., 7Bob, etc.), or reserved keywords of that language (e.g, def in Python). Characters which do not contribute towards the semantics of a program, like trailing whitespace, comments, etc. are often discarded by the scanner.

Python provides the tokenize module in its standard library to let you play around with tokens:

Python

1

import io

2

import tokenize

3

4

code = b"color = input('Enter your favourite color: ')"

5

6

for token in tokenize.tokenize(io.BytesIO(code).readline):

7

    print(token)

Python

1

TokenInfo(type=62 (ENCODING),  string='utf-8')

2

TokenInfo(type=1  (NAME),      string='color')

3

TokenInfo(type=54 (OP),        string='=')

4

TokenInfo(type=1  (NAME),      string='input')

5

TokenInfo(type=54 (OP),        string='(')

6

TokenInfo(type=3  (STRING),    string="'Enter your favourite color: '")

7

TokenInfo(type=54 (OP),        string=')')

8

TokenInfo(type=4  (NEWLINE),   string='')

9

TokenInfo(type=0  (ENDMARKER), string='')

(Note that for the sake of readability, I’ve omitted a few columns from the result above — metadata like starting index, ending index, a copy of the line on which a token occurs, etc.)

#code quality #code review #static analysis #static code analysis #code analysis #static analysis tools #code review tips #static code analyzer #static code analysis tool #static analyzer

Desmond Ivana

1595572272

What are the features of the Line clone messaging app?

The Line is a Japan-based text messaging app. It has over 250 million users worldwide, with around two-thirds of them based on Japan, Taiwan, Indonesia, and Thailand. The main perk of investing in the instant messaging app is that it gets popular within the few days of its launch. Here are the essential features of Line clone messaging app:

Profile: Users can customize their profiles, add a name, edit display picture, etc. Apart from that, an app like Line includes several privacy settings such as regulating the viewers for last seen, profile pic, status, etc.

Chat options: There are two kinds of chats available - individual chats and group chats. The individual conversations refer to one-on-one chat. A group chat allows upto 200 members in a single group. People can share videos, files, pictures, GIFs, stickers in addition to messages.

Video/voice calls: Line currently allows upto 200 members in a group call. Users can directly click on the video chat icon on the group they wish to connect and start the video call. It would be very beneficial for people as it allows conference calls with so many participants.

Security: The messages are protected so that any third party cannot view them. If the users do not feel safe with communicating with a particular user, they can block them. Then, they can send them messages.

Appdupe offers a messaging app script with all the above-mentioned salient features. Get the clone app from us, see the business growth it offers.

#line clone app development #app like line #line clone script #messaging app #line clone #line clone app

Root Cause Analysis for Data Engineers

This guest post was written by Francisco Alberini, Product Manager at Monte Carlo and former Product Manager at Segment.
Data pipelines can break for a million different reasons, and there isn’t a one-size-fits all approach to understanding how or why. Here are five critical steps data engineers must take to conduct root cause analysis for data quality issues.
While I can’t know for sure, I’m confident many of us have been there.

#data #root-cause-analysis #data-quality #data-science #data-engineering

Edmond  Herzog

Edmond Herzog

1596547800

Root Cause Analysis and Its Impact on Your Bottom-line

Global Quality Compliance leader, Shellye Archambeau says that:

Experts have estimated that COPQ typically amounts to 5–30 percent of gross sales for manufacturing and service companies. Independent studies reveal that COPQ is costing companies millions of dollars each year, and its reduction can transform marginally successful companies into profitable ones. Yet most executives believe their company’s COPQ is less than 5 percent, or just don’t know what it is.

For a company selling to consumers, 5–30% of consumers may be experiencing poor product quality — consider the cost of lost repeat sales. For B2B companies, there is a loss in credibility, cost of personnel almost continuously engaged in root cause analysis, and higher cost of manufacturing.

Most manufacturing organizations will perform statistical process control (SPC) assessment of their operations — more easily for continuous processes. For one, continuous processes have generally had sensors and control systems put in place — making such analysis easier. However, this is not enough. Many manufacturing operations, however, are batch processes; these processes often have few sensors and most data is tracked manually.

There is a large number of processes (whether continuous or batch), where SPC analysis is limited to only certain portions of the process AND the data is not digitally accessible easily. In such processes, the cost of tracking failures and performing root cause analysis is high.

A number of electronics devices are used in applications such as medical applications, critical testing, or defense, where quality is critical. The manufacturing process of many of these include use of polymers as underfill material, and sealant materials. Variability in raw material quality or processing can cause failures that would be critical.

#manufacturing #ai #quality