View source for Analytical sheet

{{infobox4
|list1=
<ul>
<li>[[Check sheet]]</li>
<li>[[Statistical process control]]</li>
<li>[[PFMEA]]</li>
<li>[[Waste level monitoring]]</li>
<li>[[Overall equipment effectiveness]]</li>
<li>[[Pareto chart]]</li>
<li>[[Information gap]]</li>
<li>[[Assignable cause]]</li>
<li>[[Check-list in project management]]</li>
</ul>
}}

'''Analytical sheet''' (also '''control sheet''') is extremely helpful in the [[process]] of collecting and [[organizing]] [[information]], which is related to the specificities of the [[product]], or process. Data about specific activities is entered into sheet to allow the study of product or process. Information about the frequency of occurrence of the events and its the place is important to further sheet analysis.

With the help of an analysis it is possible to collect specific data that can help find answers to questions such as:
* How did analyzed the problem occurred?
* How many times a specific problem happened?
* Where the problem is located?
* What is the [[cost]] of the errors?

The data can be placed into the sheet in the form of simple graphic characters. The control sheet should be constructed to be clearly seen for what purpose serves. This is a very effective and simple utility that primarily serves to collect and organize data from the performed measurements and observations.

==Types==
Very often the tool is used to monitor the process or changes that were introduced to the process by the corrective or [[preventive actions]]. The [[quality]] managers use several [[types of control]] sheets, that help analyze:
* specific features of the numerical distribution of the product or process,
* frequency of occurrence of defects,
* location of defects,
* the cost of the occurrence of faults and defects,
* the causes of defects and faults.

==Supporting tools==
There are several supporting tools that can be used to collect and analyze data related to a specific product or process. Some of the most common include:
* Pareto Chart: This chart is used to identify the most common causes of defects or problems. It is a bar chart that shows the frequency of occurrence of each problem, with the bars arranged in descending order. The Pareto principle states that 80% of the problems are caused by 20% of the causes, so the chart helps to identify the most significant problems to focus on.
* Control Chart: This chart is used to monitor and control a process over time. It shows the average and range of a process over time, as well as upper and lower [[control limits]]. Any data points outside of these limits may indicate that the process is not in control.
* Fishbone Diagram: Also called an [[Ishikawa diagram]], this is a tool used to identify the root cause of a problem. It is a diagram that looks like a fishbone, with the problem being represented by the head of the fish and the causes being represented by the bones. It is used to identify the various factors that contribute to a problem.
* Scatter Diagram: This is a chart that plots two variables against each other, with the aim of identifying any correlation between the variables. It is used to identify the relationship between two factors that may be causing a problem.
* [[Histogram]]: This chart is used to show the frequency distribution of a variable. It is a bar chart that shows how many data points fall into each category. It is useful for identifying patterns or outliers in the data.
* Flowchart: This is a diagram that shows the steps in a process and how they are connected. It is used to identify bottlenecks or inefficiencies in the process, and to help identify the root cause of a problem.

==Summary==
In summary, an analytical or control sheet is a tool used to collect and organize data related to a specific product or process. It can help track and analyze the frequency, location, and cost of defects or problems, as well as identify the causes of those problems. Quality managers use different types of control sheets to analyze various aspects of the product or process, such as numerical distribution, frequency of defects, and cost of defects. The data is typically entered in the form of simple graphic characters and the sheet is designed to be clear and easy to read.

==Examples of Analytical sheet==
* '''Quality control sheet''': Quality control sheets provide an effective way to track the quality of a product or process. It can help to identify issues in production and provide a reference for corrective action. Quality control sheets can contain data such as test results, product specifications, and inspection information. 
* '''Manufacturing process sheet''': Process sheets are used in the manufacturing industry to provide a standard reference for the production process. They contain information such as the materials and tools used, the sequence of operations, and the expected output. 
* '''Cost tracking sheet''': Cost tracking sheets are used to monitor the cost of a product or process. The sheet can contain data such as raw material costs, labor costs, and overhead costs. This information can be used to identify areas where costs can be reduced or efficiency can be improved. 
* '''Sales tracking sheet''': Sales tracking sheets are used to keep track of sales performance. The sheet can contain data such as customer orders, sales volumes, and revenue figures. This information can be used to identify trends and areas where sales can be improved.

==Advantages of Analytical sheet==
Analytical sheets provide an effective solution for collecting and organizing data related to a product or process. The following are some of the advantages of using analytical sheets: 
* Analytical sheets allow for the tracking of product or process variables over time. This insight can provide valuable data for product or process improvement. 
* Analytical sheets can be used to monitor the frequency of events. This helps to identify any potential problems or trends and take corrective action. 
* Analytical sheets can also be used to identify areas of improvement. By analyzing the data, it can be determined if any changes need to be made to the product or process. 
* Analytical sheets can be used to compare different products or processes. This helps to identify any differences that may be beneficial or detrimental to the product or process. 
* Analytical sheets can also be used to measure the effectiveness of a product or process. This can help to identify any areas where improvements can be made.

==Limitations of Analytical sheet==
Analytical sheets are widely used for data collection and analysis, however, they have certain limitations. These include: 
* '''Data entry errors''': This can occur when manually entering data into the sheet, potentially leading to inaccurate results.
* '''Limited scope''': Analytical sheets are limited in scope, as they can only collect a certain amount of data.
* '''Time-consuming''': Data entry and analysis can be time-consuming, which can be an issue for larger data sets.
* '''Lack of automation''': Analytical sheets are generally not automated, meaning a lot of manual data entry and analysis is required.
* '''Rigid structure''': Analytical sheets have a rigid structure and cannot be easily changed or adapted to suit different data sets.
* '''Inability to use large datasets''': Analytical sheets are not designed to work with large datasets, which can lead to inaccurate results.

==Other approaches related to Analytical sheet==
* '''The use of statistical methods''': Statistical methods can be used to analyze the data from the analytical sheet. This includes running tests to determine the correlation between different variables and to check for any outliers.
* '''Process mapping''': Process mapping can be used to map out the entire process, from start to finish, and identify any potential problems. This can be done with various tools, such as flowcharts, and can help identify areas of improvement.
* '''Data mining and machine learning''': Data mining and machine learning can be used to identify patterns in the data. This can be used to identify any trends or anomalies that may be present in the data and to make predictions about future events.
* '''Risk assessment''': Risk assessment can be used to identify any potential risks associated with the process or product. This can be done using tools such as decision trees or Monte Carlo simulations.

In conclusion, Analytical sheets are an important tool for collecting, organizing and analyzing data related to a product or process. Other approaches such as the use of statistical methods, process mapping, data mining and machine learning, and risk assessment can also be used to gain deeper insights into the data.

==References==
* Salih O. Duffuaa, Mohamed Ben‐Daya, (1995) [http://www.emeraldinsight.com/doi/abs/10.1108/13552519510089565 Improving maintenance quality using SPC tools], Journal of Quality in Maintenance Engineering, Vol. 1 Iss: 2

[[Category:Quality methods and techniques‎]]