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	<title>Электронный научно-практический журнал «Современные научные исследования и инновации» &#187; 5S</title>
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		<title>Development of measures to reduce the losses at the workplaces</title>
		<link>https://web.snauka.ru/en/issues/2017/02/78895</link>
		<comments>https://web.snauka.ru/en/issues/2017/02/78895#comments</comments>
		<pubDate>Mon, 20 Feb 2017 15:02:47 +0000</pubDate>
		<dc:creator>Михеева Ксения Сергеевна</dc:creator>
				<category><![CDATA[08.00.00 Economics]]></category>
		<category><![CDATA[5S]]></category>
		<category><![CDATA[Kaizen philosophy]]></category>
		<category><![CDATA[lean production]]></category>
		<category><![CDATA[loss in the workplace]]></category>
		<category><![CDATA[manufacturing]]></category>
		<category><![CDATA[Taiichi Ohno]]></category>
		<category><![CDATA[too much movement]]></category>
		<category><![CDATA[visualization and standardization]]></category>
		<category><![CDATA[бережливое производство]]></category>
		<category><![CDATA[визуализация и стандартизация]]></category>
		<category><![CDATA[Кайдзен]]></category>
		<category><![CDATA[лишнее перемещение]]></category>
		<category><![CDATA[Муда]]></category>
		<category><![CDATA[потери на рабочем месте]]></category>
		<category><![CDATA[Тайити Оно]]></category>

		<guid isPermaLink="false">https://web.snauka.ru/issues/2017/02/78895</guid>
		<description><![CDATA[In terms of sanctions and the forced isolation of the Russian economy, as well as the devaluation of Russian currency domestic enterprises face a difficult economic situation. In such circumstances, all domestic enterprises are interested in the optimization of the manufacturing process and reducing the cost of obtaining a product of appropriate quality. It depends [...]]]></description>
			<content:encoded><![CDATA[<p>In terms of sanctions and the forced isolation of the Russian economy, as well as the devaluation of Russian currency domestic enterprises face a difficult economic situation. In such circumstances, all domestic enterprises are interested in the optimization of the manufacturing process and reducing the cost of obtaining a product of appropriate quality. It depends on the quality of the finished product as well as its cost, which is important for the buyer.</p>
<p>Questions about the improvement of production processes, resource saving, cost reduction and increase in productivity are the most relevant in the industrial sector. Lean production and manufacturing are the most well-known means continually striving to improve the effectiveness and efficiency of production processes. It also eliminates all kinds of losses in the system. The philosophy of lean manufacturing is based on the idea of ​​business as a value stream for the consumer, flexibility, detection and loss reduction, continuous improvement of all activities at all levels of the organization, the involvement and development of staff in order to increase the satisfaction of customers and other stakeholders. [1]</p>
<p>The purpose of this article is to propose measures to reduce the loss of &#8220;Move&#8221; on the operator&#8217;s workplace.</p>
<p>The tasks which we are going to achieve are the following:</p>
<p>1. To study the theoretical material.</p>
<p>2. To identify the kinds of losses associated with moving process.</p>
<p>3. To determine causes of losses.</p>
<p>4. To develop measures to reduce losses.</p>
<p>5. To offer tools to reduce unnecessary movements at the working work places.</p>
<p>The concept of losses was brought by Taiichi Ohno (1912-1990), who was the Executive Director of Toyota and who set seven types of &#8220;muda&#8221;. &#8220;Muda&#8221; &#8211; is one of Japanese words, that means the loss, waste, or any activity that consumes resources but creates no value. This is an error that should be corrected. This implementation of the action, without which it is possible to do.</p>
<p>Among 7 losses there is one loss, which can be separated from the fact that it is easy to detect and eliminate, and adopted methods will give a very good result.</p>
<p>Loss of &#8220;Moving&#8221; is related to the movement of workers during the work shift. It causes to the reducing productivity, increasing fatigue and increasing personnel injuries. To reveal this hidden loss of movement of workers timekeeping &#8211; Spaghetti diagram is used. Its example is represented on the picture 1. But it is also important to understand the personal role of the worker in the optimization of his working day and his activities. We consider that elimination unnecessary movements necessary improves skills in the production process, and efficiently organize and increase competition of the worker. Personal involvement of the staff can be enhanced through the implementation of the Kaizen movement, philosophy at the enterprises. Kaizen philosophy is<br />
continuous improvement of it, starting with production and ending with the top management, from the director to the average worker. The objective of Kaizen is production without loss. The organization of work at the workplace is necessary to eliminate unnecessary movements and movements of workers eliminate disorganization of the production process. They can be quickly reduced to the minimum by moving the corresponding production equipment and operators in the cell structure. [2, 3]</p>
<p style="text-align: center;"><img class="alignnone size-full wp-image-79145" title="ris1" src="https://web.snauka.ru/wp-content/uploads/2017/03/ris12.png" alt="" width="565" height="387" /></p>
<p style="text-align: center;">Picture1 &#8211; Example of Spaghetti diagrams</p>
<p>The figure &#8220;before&#8221; presented a disorderly route on the operator workplace and irrationally arranged equipment. The figure &#8220;after&#8221; shows the result of the measures taken to address the loss of movement &#8211; correct placement of equipment and reducing unnecessary movements. [3,4]</p>
<p>We agree some scientist who suggest the following measures to reduce this loss:</p>
<p>1. Identify the causes, consequences, to calculate and develop corrective actions for the loss of &#8220;Move&#8221;.</p>
<p>2. Develop a matrix to eliminate the loss of &#8220;Move&#8221; with the proposed instruments.[5,6]</p>
<p>The most detailed loss of &#8220;Moving&#8221; is described in Table 1.</p>
<p>Table 1 &#8211; loss of &#8220;Moving&#8221;</p>
<div>
<table border="1">
<colgroup>
<col />
<col />
<col />
<col />
<col /></colgroup>
<tbody valign="top">
<tr>
<td valign="middle">A loss</td>
<td valign="middle">Causes</td>
<td valign="middle">Effects</td>
<td valign="middle">How to calculate the loss?</td>
<td valign="middle">How to fix?</td>
</tr>
<tr>
<td>Displacement</td>
<td>
<ul>
<li>irrational arrangement of working space;</li>
<li>irrational location of the equipment and containers;</li>
<li>mismatch of operations;</li>
<li>lack of standardized processes, bathrooms</li>
</ul>
</td>
<td>
<ul>
<li>decreased productivity;</li>
<li>fatigue of personnel;</li>
<li>an increase of injuries and occupational diseases.</li>
</ul>
</td>
<td>
<ul>
<li>the timing of the working movements;</li>
<li>Spaghetti diagram</li>
</ul>
</td>
<td>
<ul>
<li>optimization of the production process;</li>
<li>training of staff;</li>
<li>optimization of the equipment distribution;</li>
<li>efficiently organized jobs</li>
</ul>
</td>
</tr>
</tbody>
</table>
</div>
<p>The main causes of the losses associated with the movement are inappropriate workplace organization, poor layout of equipment, operations mismatch. All this leads to a decrease in productivity.</p>
<p>Table 2 presents a matrix of eliminating the causes of the loss of &#8220;Move&#8221;. [3]</p>
<p>Table 2 &#8211; Matrix elimination of the causes of the loss of &#8220;Moving&#8221;</p>
<p><img class="alignnone size-full wp-image-79146" title="ris2" src="https://web.snauka.ru/wp-content/uploads/2017/03/ris2.png" alt="" width="714" height="385" /></p>
<p>Loss of &#8220;Moving&#8221; was reviewed in this article. This loss exists in any enterprise, but unnecessary operator movements do not create value, so it is very important to understand what caused this loss, identify it clearly and to calculate how to remove it.</p>
<p>Knowing these highlights, you can easily reduce unnecessary fuss in the workplace, increasing the efficiency of its production.</p>
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		</item>
		<item>
		<title>Kaizen in the quality management system</title>
		<link>https://web.snauka.ru/en/issues/2021/02/94583</link>
		<comments>https://web.snauka.ru/en/issues/2021/02/94583#comments</comments>
		<pubDate>Sun, 21 Feb 2021 07:33:04 +0000</pubDate>
		<dc:creator>Рахымжан Жанна Омаркызы</dc:creator>
				<category><![CDATA[05.00.00 Technical sciences]]></category>
		<category><![CDATA[5S]]></category>
		<category><![CDATA[6 Sigma]]></category>
		<category><![CDATA[Kaizen]]></category>
		<category><![CDATA[lean]]></category>
		<category><![CDATA[sustainable development]]></category>
		<category><![CDATA[sustainable success]]></category>
		<category><![CDATA[TQM]]></category>
		<category><![CDATA[ИСО 9001]]></category>

		<guid isPermaLink="false">https://web.snauka.ru/?p=94583</guid>
		<description><![CDATA[The Kaizen method is not new, much less modern. The world learned about the Kaizen method from Masaaki Imai&#8217;s book &#8220;Kaizen: The Japanese Secret to Successful Competition&#8221;, published back in 1986. In Kazakhstan, Kaizen has been implemented with varying degrees of success for at least ten years. At present, the main ideas and methods of [...]]]></description>
			<content:encoded><![CDATA[<p>The Kaizen method is not new, much less modern. The world learned about the Kaizen method from Masaaki Imai&#8217;s book &#8220;Kaizen: The Japanese Secret to Successful Competition&#8221;, published back in 1986. In Kazakhstan, Kaizen has been implemented with varying degrees of success for at least ten years. At present, the main ideas and methods of Kaizen are widely known and are essentially classical. There is a large amount of literature by different authors on Kaizen available for sale.</p>
<p>As a result of Japan&#8217;s sluggish economic development over the past 20 years, the country has lost its superpower status, giving China second place in terms of GDP. Kaizen, which has become a classic, did not help Japan to at least maintain its previously achieved economic position in the world. Therefore, there have been attempts to reanimate Kaizen, for example, by combining it with another well-known &#8220;Six Sigma&#8221; method (see Figure 1).[1]</p>
<p><img 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" alt="" /></p>
<p style="text-align: center;"><img class="aligncenter size-full wp-image-94669" title="ris1" src="https://web.snauka.ru/wp-content/uploads/2021/02/ris12.png" alt="" width="608" height="315" /></p>
<p style="text-align: center;">Figure 1. Integration of quality management systems and methods</p>
<p>(SPC-Statistical Process Control, BPR-Reengineering, TQM-Universal Quality Management, JIT-Just in Time, Lean-Lean Manufacturing, IMS-Integrated Management System, BSC-Balanced Scorecard)</p>
<p>Although there are some attempts to present Kaizen in the form of a complete system – as a philosophy that is implemented in concrete actions, but, nevertheless, all this looks like an archaic set of techniques and wisdom, as if taken from Eastern martial arts. It is no accident that another well-known &#8220;Six Sigma&#8221; method, developed under the impression of Kaizen, directly uses terminology from karate, for example, &#8220;black belts&#8221;. Therefore, Kaizen should not be considered as an original management system, but as a methodology or program, for example, implemented within the framework of quality management programs.</p>
<p>For example, Kaizen can be very useful in quality management systems based on the international standard ISO 9001. As you know, this standard has become extremely popular all over the world (more than a million companies have implemented it) and has survived several reissues. Considering that the requirement of the ISO 9001 standard for continuous improvement causes the greatest difficulties for users, the choice of Kaizen as an improvement tool can be a good solution. And this is not accidental, since from the Japanese language &#8220;Kaizen&#8221; can be translated as &#8220;constant improvement&#8221;.[2]</p>
<p>In particular, for start-up organizations, the Kaizen tool 5S, also called the ordering method, can be very useful. Visible improvements can be achieved through the enforcement of regulations in the workplace. This is also required by the ISO 9001 standard. The order in the workplace allows you to reduce the level of defects, the number of incidents, the loss of time, raw materials, etc., as well as increase manageability. The main advantage of 5S is that it provides a foundation for creating work discipline and involving all employees in improvement programs. The 5R (5K) practice can help with ordering: Red box (Red box), Red label (Red tag), Red button (Red button), Red line (Red line), and Red light (Red lamp). These 5R tools allow you to visualize problems. The red box is filled with defective products, which are then studied and searched for the causes of problems. A red tag is attached to the waste, so that it can then be disposed of. Red button for cases of marriage in order to stop the process and prevent further marriage. The red line drawn diagonally on the items allows you to determine their correct location or shortage. Finally, the red light should indicate that a problem has occurred and that the process needs to be stopped in order to find the cause of the problem and perform corrective actions.[2]</p>
<p>Another Kaizen tool, the PDCA cycle (&#8220;Planning – Execution-Verification-Improvement Actions&#8221;), is also available in ISO 9001 and can be applied to almost any activity. The essence of this tool is in continuous sequential execution stages, from planning to execution scheduled from further verify the effectiveness and problems of implementation plans to implement improvements through the elimination of the causes of the identified problems. It is assumed that the execution of the PDCA loop never stops, as there will always be problems.</p>
<p>The most difficult part in the PDCA cycle is identifying the causes of the problems that have occurred. For this purpose, Kaizen suggests using the 5W and 5M methods. The 5W method got its name from the capital letters of the interrogative prepositions of the English language: What? (What?), Who? (Who?), When? (When?), Where? (Where?), Why? (Why?). Sometimes it is suggested to add another preposition: How? (How?). It is assumed that by asking these questions sequentially about five times, you can get to the true cause of the problem. The other 5M method gets its name from the 5 (five) supposed sources of problems: Machine (Equipment), Men (People), Material (Raw Materials), Method (Method), Measurement (Measurement). It is necessary to consistently analyze all the components of the 5M, then almost all possible sources of the causes of problems will be considered.[3]</p>
<p>Neither the PDCA cycle, the 5S method, nor any other improvement method can be implemented without the involvement of all employees. Therefore, Kaizen, like ISO 9001, requires employees to be organized into improvement teams, such as Kaizen teams, quality circles, or quality working groups. At the set time, team members gather specifically to find solutions to problems or issues in the field of quality. As a result, recommendations and suggestions are developed for senior management regarding the issues of improving the organization&#8217;s performance.</p>
<p>Kaizen, ISO 9001, and Six Sigma involve extensive use of the toolkit to implement continuous improvement programs. Start-up organizations are encouraged to first implement seven simple quality tools:</p>
<p>• A control chart (Shewhart);</p>
<p>* Histogram;</p>
<p>• Pareto diagram;</p>
<p>* Cause and effect diagram;</p>
<p>• Checklist;</p>
<p>• Flowchart of the process;</p>
<p>* Scatter plot.</p>
<p>Sometimes seven new quality tools are added to these seven simple quality tools:</p>
<p>• Affinity diagram;</p>
<p>• Relationship diagram;</p>
<p>* Tree diagram;</p>
<p>* Matrix diagram;</p>
<p>• L-shaped matrix;</p>
<p>* Arrow diagram;</p>
<p>* Graph of the decision-making program.</p>
<p>It should be noted that today there are hundreds of quality tools that are used with varying success in practice. Therefore, simple tools are more interesting for organizations that are taking the first steps to implement quality management systems.</p>
<p>The peak of Kaizen is considered to be the methods of JIT (just in time) and Lean (lean production). In essence, we are not dealing with two, but with one method of lean production, the highlight of which is to exclude any stocks both inside and outside the production cycle. The achievement of this goal is hindered by both an undeveloped supply chain and unoptimized business processes. The most difficult part of lean manufacturing relates to the organization of timely and accurate deliveries, which is associated with the existing irrational logistics system. But unoptimized business processes within an organization are completely related to the lack of knowledge and skills in process management.[3]</p>
<p>To optimize business processes, summarizing the achieved experience in optimizing business processes in Kaizen, the author of this article proposed the method &#8220;5B&#8221; (see the Journal Success No. 3(41), March-April 2008, 18-20 p.), named by him so by analogy with the above methods of 5M, 5S, 5W and so on. The essence of this method is to consistently solve 5(five) of the following main tasks::</p>
<p>To identify processes. You need to define the business processes that are required to achieve the organization&#8217;s goals. This definition includes design, planning, responsibility allocation, and process assurance.</p>
<p>Pull processes. It is necessary to ensure that business processes always meet the goals of the organization through effective dissemination of information. The usual problem: substitution of goals. For example, when an organization pursues other goals instead of meeting customer requirements, most often short-term financial benefits. Put process management in the hands of consumers!</p>
<p>Align the processes. As a rule, the process elements are not consistent with each other, usually in terms of performance. This causes unevenness, delays, inventory, product spoilage, and many other losses. Ensure the flexibility of the processes so that the processes can meet any changes in requirements!</p>
<p>Squeeze out processes. As a rule, business processes and their environment contain a lot of things that do not add value to the products produced. Extra traffic, extra equipment, extra people, garbage, supplies, etc. constantly create problems. Eliminate all unnecessary things, for example, using the well-known method 5S.</p>
<p>Clean up the processes. Any business processes are subject to risks associated with external and internal influences. These can be uneven and / or unreliable supplies, unreliable and incompetent employees, unreliable and inappropriate equipment, safety and environmental issues, and so on. To ensure that the processes are stable, regularly identify and eliminate the causes that cause the variability (instability) of the processes![3]</p>
<p>It is very important to follow the sequence of solving problems &#8220;5B&#8221;. If, for example, you immediately start solving the last problem, then the variability of the process will be enormous! The reason is that business processes that have not undergone initial optimization (pulling, leveling, and squeezing) are extremely variable in their status.</p>
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