- In the context of this paper the adaptation of the classical Lean methods to the automated and ultramodern manufacturing processes of modern production is to be carried out. The Lean methods were developed in the automotive and mechanical engineering industries, so that they can often only be used to a limited extent for modern, highly automated mass production.
INTRODUCTION
While Lean in the early years largely dispensed with information technology development, an important part of the third industrial revolution was the development of enterprise resource planning systems. The basic goal of an ERP system is to efficiently and effectively manage, influence and design the resources of all business areas. This paper will show a Lean exploration related on the focused methods of the hidden industries in the European union. So the mindset for a Lean shopfloor which could be automatized and provided by an successful ERP implementation.
Lean Management has been an established and efficient
management tool since the end of the 1980s and enjoys great
popularity in mechanical engineering and automotive
engineering. During a period of more than ten years, clear
tendencies can be observed that companies from other
branches of industry as well as service companies are using
Lean Management approaches to make their business
processes significantly more efficient. From their own
experience and coordination with other Lean experts, the
idea has grown to review and evaluate the transformation and
applicability in other areas. The problem of this research
focuses on the manifold variance of various production
plants and the interactive interface between human efficiency
and personnel optimization, as it is required in Lean
Management, as well as the logistically optimized production
area. Only the areas of production and process development
is considered, as the utilization factor is estimated at its
highest and a consideration of all operational processes in the
context of this article is estimated as not manageable. For
methods with problems in the application [
• • • • •
This shows a certain synergy effect which is controversially discussed in specialist media. This is due to the fact that the introduction of ERP systems works successfully in only 39% of cases, every fifth project fails and around 64% of all projects are too tight in terms of time.
This shows that there is clear potential for improvement even
during the introduction of ERP systems. For example,
organizational methods such as FiFo, Just in Time, Just in
Sequence, Kanban, Poka Yoke, Muda, Muri or even 5S [
Extensive research by the Kufstein University of Applied Sciences under the direction of Prof. Dr. Martin Adam shows that almost half of ERP manufacturers support Lean Management in their software, but only a fraction of users use the functionalities. In his PhD thesis, Dr. Daryl Powell describes the connection between Lean and ERP as a paradox. As an example, he cites the controversial goals of fixed lead time for ERP in contrast to one-piece flow and just-in-time. With regard to this Symantik the inclusion of Lean in ERP systems is again not possible. Furthermore, he shows in his work that since the 1990s the demands placed on manufacturing companies have continued to change and that Lean Management requirements must be mapped in relation to a successful company. Modern ERP systems support this.
Lean Management has been used successfully for many years and has many supporters as well as some opponents.
The same can be shown for the application of Lean Copyright © 2020 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).AESP20: 1st Management methods in the implementation and use of ERP systems by referring to the selected sources. In the following exploration, the optimal methodical Lean setup for the individual industries will be determined, which can be used both in the pre-structuring before the ERP implementation or in the ERP system for each industry.
The NACE classification, the statistical classification of
economic activities in the European Community (French:
Nomenclature statistique des activités économiques dans la
Communauté européenne) was developed by the European
Union on the basis of the ISIC (International Standard
Industrial Classification of all Economic Activities) of the
United Nations. [
As the work draws its experimental focus from semiconductor and microsystems engineering and data processing and digitalization, Division 26 of the NACE classification has deliberately been divided into three subgroups: data processing, electronics/optics and semiconductors/MST. Divisions 10-18, 22-25 and 27-30 are completely preserved in their meaning, only their names are simplified. Divisions 19-21 have been combined under the generic term of the chemical industry, since the chemicalpharmaceutical industry is also spoken of in professional associations and similarities are assumed in the shop floor.
With this separation of the industries related to a successful Lean Management method implementation the pre-job for ERP projects is done. Each company could be provided before starting an ERP implementation project with the best acting methods for optimizing the company. CA CB CC CD CE CF CG CH CI CJ CK CL CM 10 to 12 13 to 15 16 to 18 19 20 21 22 to 23 24 to 25 26 27 28 29 to 30 31 to 33
While in Germany and Austria there is compulsory membership in the chamber structure for many areas, in Switzerland there is no comparable obligation in the chamber and economic structure, which makes it difficult to consider all German-speaking countries. For this reason, the consideration in Switzerland is left out and only the Germanspeaking area of Germany and Austria is considered. The focus for ERP implementation is set in the German speaking area, so with the substitutional choosing of the most important industries this set up with the twelve biggest sectors is used.
The explorative cross-industry research is carried out
with a survey of fifteen Lean experts from industry and
science. The most of them also have and process and
enterprise resource planning background. 15 experts are seen
as the lower optimal limit of specialist interviews. In
preparation, a research of all available Lean methods was
carried out. The identified Lean methods were then described
and defined. This elaboration is then implemented in the
interview guideline in order to provide the Lean managers
with clues for possibly unknown methods. [
optoelectronics company of a leading Production engineer of a leading optoelectronics company Head of microtechnology training at a world-leading technology group Plant manager of a medium-sized electronics company in the Upper Palatinate Production technician of a worldwide leading automotive supplier Production manager of a German pressing plant
IT production expert for a European pharmaceutical company Project engineer and member of the examination board for production technology at an educational institution in Bavaria Head of a Master's programme in Business Process Management at an Austrian university of applied sciences Professor for Operations Management at a German University of Applied Sciences Professor of Industrial Production at a State Academy of Studies Professor of International Management and Head of an Institute for Management and Information at a German University of Applied Sciences Professor of General Business Administration at a Hungarian University Senior Process Engineer of a leading optoelectronics company
The questionnaire asks 51 of the most common Lean methods. The methods have been researched in detail. After initially identifying 100 Lean methods, 51 methods were retained after shortening the methods with the same content but different names and combining combined methods. For each question, the interviewee should decide whether he/she
The three-dimensional survey shown must be carried out for each method in the areas of production and production development. From the approach of the survey several directions of answers result, which are composed as follows: • • • • • • • • • • • • • • • • • • has his/her own experience with the method and how he/she will look into its applicability in the simplified industries.
The evaluation is to be carried out in whole numbers
from "1" to "10" for one's own experience and each industry.
Levels 1-3 indicate that the method is applicable; 4-7
corresponds to a partial, i.e. problematic, applicability of the
method. 8-10 indicates that the method is not applicable. The
gradations within the answer groups should give the
participant the opportunity to create gradations within the
group. The levels should have the following description [
2: The method can be used without restrictions, an introduction to the topic is required.
3: The method can be used without restrictions, further training in the subject is required.
4: The method is partially applicable, small modifications for the application must be made.
5: The method is partially applicable, modifications for the application must be made.
6: The method is partially applicable, larger modifications for the application must be made.
7: The method is partially applicable, large modifications for the application must be made, the application usually shows no success.
8: The method is not applicable, although the structure corresponds to an applicability.
9: The method is not applicable, the structure would have to be changed significantly to make the method applicable.
10: The method is not applicable; no possibilities are seen to modify this method to make it applicable.
It is analysed whether there are significant differences in
individual methods and where the median and the arithmetic
mean are located. At the same time, the standard deviation
and the number of participants and experts in this field are
noted and compared, as it were, from which area this
evaluation comes. [
The evaluation of the explorative analysis is carried out using simple statistical means. Since a complete statistical evaluation with distribution considerations is very difficult for a maximum of 15 participants and industries, some of which are only represented by one participant, and since statistical certainty is far from being established in the population as a whole. Since a distribution can only be tested with great uncertainty with such a small number of participants in an exploration, a comparison is made here between the mean value, standard deviation and median in relation to the response of all experts and the response of the experts within the industry. The evaluation is carried out using Microsoft Excel and Camline Cornerstone. Since a number of 15 participants is far from representative of the entire population, no typical distribution functions are used here, but only a simple statistical evaluation is carried out to evaluate the significance of the answers of all specialists. By looking at the standard deviation in relation to the mean value, it is shown, even with a small sample of n maximum 15, how large the dispersion of the results around the mean value is.
In order to exclude this effect in the survey, the mean and median are used. After collecting the data, the mean, median and standard deviation are calculated for each question group. Depending on whether the mean value and median are very different, a larger dispersion of the values can be assumed. In the comparison of the arithmetic mean, the result of which includes all distributions of the results, with the median, which lies centrally in the absolute numbers of the values. If both values deviate from each other, this indicates that there is no equal distribution on both sides around the mean value. In the overall consideration of the subtraction/addition of the mean value with the standard deviation in comparison to the median, a fundamental statement can thus be made about the certainty of the result and the dispersion of the answers. Further consideration of the standard deviation gives an impression of the width of the distribution in relation to the position of the mean value compared to the distribution shift in relation to the median. The decision of the evaluation is made according to the description.
From this statistical statement, the methods are identified which have to be analysed in the qualitative part of the work. Based on this description, the authors formulate hypotheses, which should form a suitable basis for the expert evaluation. These hypotheses represent specific relationships between the individual areas.
The methods that are confirmed with "pass", a green mark, are not subject to further investigation for the time being. Methods marked with "partial", a yellow mark, must be worked on in the expert workshop. The experts are expected to provide a qualitative statement and a response based on their experience. Thus, the artefact is also based on an expert report. For each individual sector, the mean is evaluated in column "2", the standard deviation is calculated in column "3", the mean is added to the standard deviation in column "4" and subtracted in column "5". In the sixth column, the median is calculated. Column "7" contains the number of responses for this area and column "8" defines how many experts from this industry participated.
In addition, a quotient is calculated, which defines the proportion of survey participants in relation to the participants from the industry. This figure gives a qualitative impression of how representative the industry is. In column nine, the number of responses is divided by the number of experts in the field. This ratio is used to determine a certain degree of certainty in the statement. If there are factors greater than 100%, this answer was answered by more participants than by specialists in this field. If the factor is greater than 0% but less than or equal to 100%, fewer participants answered this question than specialists in this field are available. If the value is exactly 0%, no expert has evaluated this industry.
The visualisation of the evaluation of the explorative survey is carried out with the help of a table and two diagrams per examined method. In the table, the mean value, the standard deviation, the standard deviation are subtracted from the mean value, the mean value plus the standard deviation, the median, the number of participants, the industry, the number of experts per industry and the factor described above are determined for the individual industry sectors and the individual experience. The evaluation is carried out according to the criteria of safe applicability, applicable, partially applicable or not applicable. The first diagram serves as a statistical representation of the method. The crossed line in the middle visualizes the mean value of the method. The wide bars describe the confidence interval around the mean with plus and minus a standard deviation. The boundary points describe the extreme values of the evaluation. With the help of this diagram, the statistical representation of the methods is to take place and a clear evaluation is to be represented. The second diagram shows the mean value, the median, the mean value plus the standard deviation and the mean value minus the standard deviation. This should help to illustrate whether the method is about a very large dispersion or whether the mean and median are far apart or close to each other, this should give an indication of the distribution of the answers and show the reader whether there is a continuous or statistical fluctuation over the small number of participants in the exploration.
III.
In general, automotive technology and semiconductor and microsystems technology are best represented. This is because Lean Management is most widespread in automotive engineering. The electrical engineering, mechanical engineering and electronics and optics industries are still well represented, with two participants each. One representative will be provided from the fields of metal construction, plastics, data processing, food and chemical industry. There will be no representatives from the textile and wood industries. Thus, the results can be well represented for the industries of automotive engineering, electrical engineering, metal and mechanical engineering, which are widespread in Germany and Austria, as well as for many adjacent industrial sectors such as the semiconductor industry, the food industry or the electronics and optical industry. Uncertainties in the valuation are seen for smaller branches of industry such as the wood industry or the textile industry. Industries with very high valuation factors such as the chemical industry, the food industry, data processing or the plastics industry should also be critically evaluated in the exploration sector. For many methods, it can be seen that they can be applied across all areas. Particular importance should be attached to these methods, which differ widely in individual sectors. Elektrotechnik Maschinenbau Metallbau Kunststoff Datenverarbeit.
Elektronik/Optik Nahrungsmittel Chemieindustrie Textilindustrie Holzindustrie Erfahrung Halbleiter/MST Elektrotechnik Maschinenbau Metallbau Kunststoff Datenverarbeit.
Elektronik/Optik Nahrungsmittel Chemieindustrie Textilindustrie Holzindustrie Erfahrung Halbleiter/MST Datenverarbeit.
Datenverarbeit.
Elektronik/Optik Datenverarbeit.
Erfahrung Halbleiter/MST Maschinenbau Metallbau Datenverarbeit.
Nahrungsmittel Chemieindustrie Textilindustrie Datenverarbeit.
Halbleiter/MST Datenverarbeit.
Erfahrung Halbleiter/MST Elektrotechnik Kunststoff Datenverarbeit.
Elektronik/Optik Nahrungsmittel Chemieindustrie Erfahrung
In the following chapter the partial and not usable methods are presented. For the ERP setup it’s good to see that there is not sucha big variance in the methods. The focus is more on some not usable methods. For implementing efficient and optimized ERP processes and setups a setup of around 45 to 50 Lean methods can be used. ERP provider should be used the LM methods in two ways. Value stream and process structured methods, like value stream mapping or Chaku Chaku, should be used inside the ERP systems as process managing support. On the other side the easy to use and shopfloor optimizing methods should be part of each ERP implementation project, because the shopfloor and the logistics are more leaned and structured. So the implementation is easier and faster. Methods with partial or not usable ratings
Hypothesis 1 (Many methods follow general approaches and are fully applicable in all industrial sectors): The largest single area of evaluation is shown by the applicable methods. This confirms the first hypothesis that many methods are fully applicable and each ERP implementation could use this methods for optimizing and implantation in ERP software. A positive aspect of the general use of Lean Management in all industries is that there are no methods that are not applicable. Conversely, this means that for all methods examined in the context of this research question, there is an applicability or at least a partial applicability for each method in each industry.
Hypothesis 2 (A small proportion of Lean methods show problems in implementation in all industrial sectors due to their complexity.): The second hypothesis is limited by the fact that there are no methods that are not applicable. Thus at least everywhere a partial applicability is given. However, there are methods that show predominantly partial applicability in all industries and thus speak against a simple implementation due to the complexity of the methodology. This hypothesis is thus partially confirmed. This methods could be analyzed and used for the ERP implementation in industries with significant positive results.
Hypothesis 3 (Methods that relate to the logistics process
within production show significant differences in the
individual industries): The only exceptions are the Kanban
and FiFo methods, which can be applied in almost all
industries, at least according to the qualitative analysis. Other
logistic methods such as Chaku Chaku, Hejunka, Just in
Time, Milkrun, Mizusumashu [
Hypothesis 4: (Lean experts and internal users as well as end users have a differential perception of usability, based on different interpretations). The fourth research hypothesis is also confirmed, since significant differences have occurred in various methods. Thus, the assumed research questions, which arose from practical experience, can largely be regarded as confirmed, except for the second hypothesis. With this research model, a fundamentally successful attempt was made to confirm or refute the four hypotheses. The research model has proved successful in its application and could use in different ways. Only Lean implantation could be one part of the use, on the other hand the combination with ERP topics for restructuring the shopfloor and implementing Lean ERP software is very helpful.
For further research, it would therefore be necessary to
set up a working group on industry-related colleges,
universities and employers' associations that can work with
the necessary access to the whole. The expansion of the work
should take place both in the research design and in the
extension to service and health sectors or also the public
sector, in order to consider the overall economic
effectiveness. It should be mentioned here that the literature
research of the theoretical part shows that Lean Management
finds more and more applications in the areas of Health Care,
Administration, Green and Sustainability and Services. Also
the setup in ERP models and ERP software is growing and
discussed. The public sector also includes many
administrative areas and could benefit significantly from
Lean Management approaches in the workflow. This work
provides a first insight into the industrial sectors, a similar
approach for non-industrial sectors is identically possible and
also a big customer sector for the ERP business. Many
research topics from recent years have dealt with
implementation determination, Lean design approaches or
evaluation models for the transformation of Lean
Management in various industries [