CC BY
39
УДК 528.48
Фолькер Швигер, Ли Чжан, Йюрген Швейцер
Технический университет г. Штутгарта, Института прикладной геодезии Германия
МОДЕЛИ ОЦЕНКИ КАЧЕСТВА ИНЖЕНЕРНО-ГЕОДЕЗИЧЕСКИХ РАБОТ И ИХ ПРИМЕНЕНИЕ В СТРОИТЕЛЬСТВЕ
Volker Schwieger, Li Zhang, Jurgen Schweitzer
University of Stuttgart, Institute of Engineering Geodesy (IIGS)
Germany
QUALITY MODELS AND QUALITY PROPAGATION IN CONSTRUCTION PROCESSES
Key words: Quality Model, Construction Process, Engineering Geodesy Process, Petri-Net
SUMMARY
In general, engineering geodesy has a strong relationship to construction and especially to construction processes. It is responsible for surveying and setting out as well as for monitoring tasks. Engineering geodesy delivers the geometric base for the construction process. Additionally, it controls the results of the process. Besides, engineering geodesists have a broad knowledge regarding quality models, quality parameters as well as quality propagation. With respect to other disciplines like transport telematics or electronic engineering, the quality characteristics and parameters are different. In comparison to construction engineering the quality description is already advanced, since construction quality means to avoid quality defects by keeping the given tolerances. This leads to the conclusion that there is a need for quality models and propagation methods at the borderline of construction engineering and engineering geodesy, with other words within the construction process.
This article focuses on two research projects currently carried through at the Institute of Engineering Geodesy at the University of Stuttgart (IIGS). Both deal with the complete description of quality within the construction process. One focuses on fundamental research and congruously on the detailed quality description of engineering geodesy processes on quality parameter level based on a complete quality model. Here the mathematical correct quality parameter propagation is realized by different methods, e.g. Monte Carlo Simulation leading to reliable information at the interfaces to the construction process. The other project is application-oriented and focuses on the Total Quality of the entire process, taking into account the product, too. The quality model is application-oriented and simplified in
order to take into account the needs of the Small and Medium Enterprises (SMEs). The quality is measured on a rough scale using so-called checks. The first project is applied to the engineering processes that are needed for climbing formworks, and the second to the construction of residential houses. The article compares the two projects, presents the respective advantages and disadvantages and shows the interrelationships.
INTRODUCTION
Quality is an important characteristic related to any product and to any process. This applies to economy, since “good quality” is a criterion to buy a product. But it also applies to science, because nobody would trust in research results that are not evaluated with respect to their quality like accuracy and correctness.
Geodesy and engineering geodesy had and have a strong focus on quality since the early days. Nevertheless a complete quality model considering processes and products does not exist. The same is valid for civil engineering, especially construction processes. In engineering geodesy the theory of geodetic networks comprises the characteristics accuracy, reliability, and sensitivity, but is restricted to a very narrow domain: the geodetic networks. In civil engineering the only known quality parameters are tolerances.
To obtain a broad idea how such a model looks like in theory and practice, it is necessary to have a look at the neighboring disciplines like civil engineering software development, data management and transport telematics. At the IIGS a model with two-tiers (characteristics and parameters) was developed for transport telematics (Wiltschko 2004). This is the base for the models described in the following.
This article focuses on two research projects currently carried through at IIGS. Both deal with the complete description of quality within the construction process. One focuses on fundamental research and congruously on the detailed quality description of engineering geodesy processes on quality parameter level based on a complete quality model. Here, the mathematical correct quality parameter propagation is realized by different methods, e.g. Monte Carlo Simulation leading to reliable information at the interfaces to the construction process. The other project is application-oriented and focuses on the Total Quality of the entire process taking into account the product, too. The quality model is application-oriented and simplified in order to take into account the needs of the Small and Medium Enterprises (SMEs). The quality is measured on a rough scale using so-called checks. The first project is applied to the engineering processes needed for climbing formworks and the second to the construction of residential houses. The article compares the two projects, presents the respective advantages and disadvantages and shows the interrelationships.
DEFINITION OF QUALITY
Quality is an important feature needed for the description of products and processes. In general the quality description of products is well known, despite the
fact that the quality description of processes is not familiar to everybody and therefore needs more concentration within research. Within this paper the authors will deal with both components. According to DIN EN ISO 9000 quality is the “degree to which a set of inherent characteristics fulfils the requirements” (DIN EN ISO 9000, 2005).
The basis of each quality management system and each quality assurance measure should be a well-justified quality model that is product- as well as process-related. A quality model is a conceptual framework in which the abstract term of quality is gradually divided into individual aspects and thus the abstract term is substantiated. When using a quality model the quality of a product or process should be completely describable and comparable. This means that you need a theoretical definition as well as the realization of this theory by measurable parameters that can be used to define requirements too. For some quality models, e.g. for data management (ISO 2001) a three-tiered model is in use justified by this application. Regarding the construction applications as well as examples from the transport telematics domain (Wiltschko 2004), a two-tiered model is considered to be suitable. Quality is defined by different characteristics that are purely conceptual. One level lower the parameters describe the measurable quantities that are used to quantify the quality of a product or a process. For engineering geodesy the best known characteristic is accuracy. Parameters to substantiate accuracy is e.g. the well-known standard deviation. Despite this, in civil engineering the only known parameters are tolerances that substantiate the characteristic correctness.
Quality
requirements /product definition
characteristics structure
parameter
substantiate
qua 1 i t y model
Figure 1: Definition of a quality model (Schweitzer & Schwieger 2011)
Fig. 1 represents the relationship between characteristics and parameters, and the term “quality” is presented in conjunction with a quality model. A quality model
should be complete according to the actual group of products or processes, this means that it is driven by the application. All requirements should be represented by characteristics and parameters.
The parameters are quality measures which describe the quality by means of parameter values. In Table 1 the possible parameter types according to ISO/TS 19138 (ISO/TS 2006) are given.
Table 1: Parameter types for the quality model (Schweitzer & Schwieger 2011)
Parameter type Definition Example Value type
measure Number or quantity that records a directly observable value or performance. All measures have a unit attached to them. 5 cm, 0.01 gon real
indicator Indicator that presents a binary yes/no answer for an item True / False boolean
count Total number of items that are subject to yes/no decisions 5 integer (1..n)
rate Number of yes / no decisions with respect to the total number of items 5:10*100 = 50 % percentage % (0..100)
QUALITY IN CONSTRCTION PROCESSES
Project Background
The project QuCon „Development of a Real Time Quality Support System for the Houses Construction Industry“ is granted within the EU CORNET Programm and showed a life span from February 2009 to January 2011. Currently the final reports are written. CORNET is a network for information exchange. It creates opportunities to set up transnational collective research and to promote close cooperation between the responsible national/regional ministries and agencies across Europe. The research is focused on the necessities of small and medium sized enterprises (SMEs) and therefore is application-oriented.
The main goal of QuCon was to develop a cost-effective innovative real-time quality assurance tool suitable for the houses construction industry. The main objectives of the project were:
- Investigating and analyzing the building process from project initiation to commissioning,
- Developing a quality model and quality parameters as well as assurance indices,
- Optimising the indices with respect to time and money,
- Developing a prototype software appropriate for SMEs.
The project management is mainly effected by „Federation for Quality Research and Science“ (FQS, Germany) and the partner association „Cyprus Association for Quality“. There were four work packages dealing with the main obj ectives described before.
The IIGS was cooperating with the other research partners: the Frederick Institute of Technology and Synectics Ltd, both from Cyprus. The participating SMEs of Cyprus and Germany were directly integrated into the project in so called SME-Meetings, where the research results were intensively discussed. The focus of IIGS within this project was the development of a consistent quality model for the building of residential houses. This quality model distinguishes between quality of products and of processes; the characteristics are partly concretized with parameters. The model is able to calculate the quality assurance indexes in real time and in postprocessing.
The targets of the project are enteirely reached. At first the prototype software has been presented to the Cyprus SMEs. Curently the same is realised for the German SMEs.
Quality Model
The developed tool of QuCon should help the SMEs not only to improve the final product, but also the quality of their work (processes). For this reason an intensive discussion took place and the project team defined a complete quality model for construction processes for residential houses. Later on, when the characteristcs should be substantiated by parameters, the participating SMEs realize the need for a more simplified model well-suited for practical applications in their enterprises. Despite this final decision the authors present all inherent characteristics of construction processes in this paper. For exemplary parameters and measurement methods the autors refer to Schwieger et al. (2010). Finally the reduced application-oriented model is presented.
Process related quality characteristics
Expense: Adherence to the expense plan. The (sub-) process is carried out within / exceeds / falls below the budget.
Timeliness: Adherence to the time schedule. The (sub-) process begins and ends at the scheduled points of time / shows a time delay / is ahead the time schedule.
Process-Correctness: Adherence to the predetermined procedure. The predetermined procedure regarding the correctness can be deduced from laws, standards, the generally recognized codes of practice and the technical demands written in the contract. Correctness is regarded with respect to the technical demands; e.g. correct sequence of working steps or of compliance with all regulations. These criteria may be fulfilled, partly fulfilled or not fulfilled.
Resources: Adherence to the predetermined resources. The (sub-) process is carried out within/ exceeds / falls below the predetermined resources. In any case the resource rate has an influence on the timeliness and on the expenses, since any lack in resources lead to an increase of expenses or of the time spent, or of both.
Synchronization: Adherence to the overall predetermined inter-process workflow. This quality characteristic addresses different processes that depend on each other. These (sub) processes begin and end at the scheduled points of time / show a time delay / are ahead the time schedule with respect to the related processes.
Product related quality characteristics
Availability: Overall quality characteristic that takes into account all other definitions. Product is completed at the required point of time within the budget using the planned resources. The characteristic is not purely product related. It is the combination of process- and product-related characteristics.
Completeness: Adherence to defined completeness of product. Product is completed correct as defined and planned or it is fragmentary.
Condition: only correctly realized products are counted as completed.
Product-Correctness: Adherence to demands, requirements, standards,
generally recognised codes of practice and technical demands written in the contact. The demands, requirements, standards, etc. are fulfilled or not fulfilled. Two variants have to be distinguished:
а) The correctness of the product is measurable. These characteristics can be parameterized using accuracy parameters. If their accuracy exceeds the tolerance from the standards, demands, etc., the product is incorrect.
б) Some characteristics are not measurable. In these cases there are checks only, e.g. visual controls. If requirements are not fulfilled, the product is incorrect.
Accuracy: Degree of adherence to demands, requirements, standards, generally recognized codes of practice and technical demands written in the contract. Accuracy is the basis for correctness decisions of variant a) of product-correctness. In general it takes into account random deviations only.
Reduced application-oriented quality model
The quality characteristics (resources, synchronization and process-correctness) were eliminated after taking the requirements of the SMEs into consideration. Finally, the product characteristics “completeness”, “correctness” and “accuracy” as well as the process characteristics “expenses” and “timeliness” were considered. Fig. 2 shows the basic structure of this quality model. The availability is equivalent to an overall quality characteristic,, which takes into account all other characteristics and thus it is defined differently with respect to e.g. Wiltschko (2004). The use of the process-related characteristics is elective. The German SMEs are eager to include these characteristics. For the Cyprus case the team firstly excluded them from the model. After the feedback of the SMEs at the end of the project the team is considering to include these two characteristics again.
Figure 2: Basic structure of reduced QuCon quality model (Schwieger et al. 2010)
The process-related characteristics are substantiated in the following way: Expense rate
E)
^exP _ _______]_
1 ~ Ea
(1)
with E actual expenses and Eb budget (planned expenses) for checkpoint j (compare 3.4),
Timeliness rate
rj^b
ST-YJ (2)
with Ta actual time consumption and Tb planned time consumption for checkpoint j (compare 3.4).
Obviously both parameters show “good values” for ER and TR respectively, if values of one or even higher. The second is almost never happening for construction processes.
For the product-related characteristics the authors refer to (Schwieger et al. 2010) and the actually used simplification by check items, check lists and check points described in section 3.4.
Process Model
The measuring of process-related quality parameters requires a process model. Additionally, methods for quality propagation need an understanding of the underlying processes. In the context of the project QuCon the constrcution process for residential houses has to be modelled.
The whole construction process has to be subdivided into the processes (first level) as well as sub-processes (second level) and activities (third level). The level of detail has to be chosen according to the possible amount of standardization. If many deviations from the standard process occur on a more detailed level, e.g. activities, it
is easier to describe the process less detailed and omit the activity level. Besides, the less detailed approach is more suitable for SMEs.
Construction process (classic)
Preparation of construction
1 '
Carcass construction of earthwork
1 f
Carcass construct on of basement
1 '
Carcass construct an of ground floorer the other star es}
1 F
Carcass construction of attic story
1 '
Internal extension
1 r
External extension
Figure 3: Total construction process for residential houses (Wengert & Schwieger 2010)
The construction process model consists of about 100 sub-processes. However, the scientists and the SMEs from Cyprus have another view on the process. They have designed a more detailed construction process model which contains more than 500 sub-processes and activities. The total construction process is split into 7 main processes which are shown in Fig 3. Fig. 4 presents the flowchart of one main process: the carcass construction of earthwork with its sub-processes and some exemplary checkpoints (compare next section).
The process is modelled as flow charts (Fig. 4) and as Gantt charts showing the dependencies among the sub-processes (e.g. Schwieger et al. 2010). Both are simple visualizations of the process to guide the construction manager through the process and suppport the respective management tasks. This sort of modelling does not allow for
mathematical propagation of quality paramameters through the process. A simplified approach for the propagation task will be presented in the following section.
Figure 4: Example for sub-processes of residential houses: carcass construction of
earth work (Zhang & Schwieger 2011)
Quality Propagation
Fig. 4 already indicates the checkpoints for the process (yellow boxes) which are important to compute quality measures in real time. These checkpoints can be drawn from the needs and requirements of the contract, standards, guidelines, general recognized code of practice as well as laws (compare Schwieger et al. 2010). One example is the checkpoint excavation. Here, e.g. the excavation depth is measured carefully with the levelling instrument.
Each checkpoint consists of a number of check items that can be scored according to their quality level. Each of the check items is allocated to one quality characteristic (completeness, correctness or accuracy). Besides the check items are classified into visual checks, measurable checks and functional checks in order to fix the score scale. The score ranges from one to five for measurable checks that include accuracy parameters (table 1: transforming a measure into a non-binary indicator) and to one or five for all other check items (binary decision or according to table 1 an indicator respectively). One means ”check not passed”. In the second case of the binary decision, five is ”passed” If, as in the first case, five steps exist, two is
’’passed” and the other steps are quality parameter values that overexceed the minimum value more or less significantly.
The overall product quality score for one checkpoint is determined as the weighted average of all check items belonging to one checkpoint. The weights are defined according to the costs (Zhang & Schwieger 2011). Additionally, all check items are grouped in check lists that belong to one craft. This is not important in teh context of this paper, but delivers the possibility to evaluate craftsmen. Check items of one checkpoint may be based on one check list only, but do not have to do so. This weighetd average is the score for the product-related parameters at this checkpoint.
The determination of the total quality index (availability index) is realized mainly by the weighted averages using the score mentioned before.
_ Sc°™, Scnj and S“j are the scores of check items (in checkpoint j) for completeness, correctness, accuracy
- W™™ ^Jand Wny are the weighting factors of check items (in checkpoint j)
for completeness, correctness, accuracy,
- Ncom,Ncorand NjCC are the total numbers of the check items for completeness, correctness and accuracy in the checkpoint j
- SJ'1", .V""'and Sjcc are the product-related quality scores of checkpoint j, they will be determined in the scoring system using equations (3) to (5):
n=N‘
com
X Tjr com rycom
L Kj ■snj (3)
Qcom n=1
n=NCj°m
V w°
n,
n=1
\ ' Tjrcor ryCOr
la W«,J 'Sn,J (4)
1 n=N\
" rcom
n,j
n=1
n=Nc°r
cor _ n=1
gcor ____
J n=N\
’ tCOT
n>j
acc _____ «=1
gacc ____
V w°
/ J n,
n=1
cc
Ejjracc ci acc
w«,s 's«,j (5)
n=1
n=Nfc
J n=Nf
racc
n,j
y W“
n,
The score of product related quality characteristics expense and timeliness can be determined by the comparison of actual and planned expense and time
W exp Wtime
consumption as shown in section 3.2. The weightings j and j can be defined by the users, because each user has his own estimation of the importance of the expense and timeliness compared to the product characteristics. The score gives the users just an overview of the quality, so it is no problem if the weighting factors are different from user to user or from company to company. The authors propose for
fi=l
J^exp _ jytime _ Q 5 WexP + Wtime - \
1 1 (so that J ' ) to assure that product and process related
characteristics are weighted in the same way.
To combine product and process quality measures, the user has to estimate an overall quality index (availability) as an overview. The scores of product characteristics are between 1 and 5, but the scores of the process characteristics are around 1. For this reason, the score of product characteristics should be divided by 5, so that they are also around 1. The weightings of the product characteristics depend on their percentage of the check items. They are different from checkpoint to checkpoint. But their sum is constant: WJ"" + WJnr + Wp:c = 1. Consequently, the total
quality index will be estimated
$com scor sa
£java _____
'J—. wcom + 1 ■ Wcor + 1 ■ Wacc + Sexp ■ Wexp + Sttme ■ Wtime
5 } 5 } 5 } J J J J (6)
jycom + jycor + jyacc + j^rexp + jyti,
n=N'i
" rcom
nj
yy-com _ ____________________________n=l
IK
J n=Nc,om n=Nfr n=Nfc (7)
acc
n,J ' ’ ’ n,j
n=1 n=1 n=1
y wcom + V wcor + V w
Au n,j / J n,j / J r
n=1
n=Nj°r
Zwcor
n,J
Wcor = ■
n=1
1 n=Nj°m n=Nc" n=Nfc
V Wcom + V Wcor + V Wacc
L-i n,3 Lu n,3 Lu n,3
(8)
n,3 Lu nj
n=1 n=1
n=N\
' racc
nj
yyacc — n=\
Y r;
__ ______________________n^\_______________________________
■/ ~~ n=Nfm n=Nj°r n=Nfc (9)
v wcom + v wc°r + y wacc
L-i n,3 t—i n’3 Au n,3
By using the checkpoints, the construction process will be closely linked to the scoring system (compare Fig. 5). The inspector on the construction site can score the check items within the checkpoints on site and put the planned and actual expense and time consumption in the system, and then the scoring system can run automatically.
n=\
Figure 5: Construction process and scoring system (Zhang & Schwieger 2011)
QUALITY IN ENGINEERING GEODESY PROCESSES Project Background
The project EQuiP (Efficiency Optimization and Quality Control of Engineering Geodesy Processes in Civil Engineering) is a project which is granted by the German Research Foundation (DFG). Consequently the project deals with fundamental research. The main content is the efficiency-orientated integration of engineering geodesy processes into construction processing, considering measures of quality assurance. The main focus at the IIGS lies on the quality model and quality assurance. The work at IIGS has started in June 2009 and is still ongoing. The partner institutions are the Geodetic Institute Hannover, the Institute of Construction Informatics Hannover and the Institute of Construction Management Stuttgart. The working packages of the first two-year-phase are “Construction Process Analysis”, “Development of a Geometry-related Quality Model”, “Development of an Efficiency Model”, “Simulation and Evaluation of the geometry-oriented quality assurance process and of optimization strategies”.
Currently the IIGS has developed a parameter-based quality model and is developing a quality propagation method on the base of a process model for engineering geodesy processes. This will be realized exemplary for climbing formworks of high-rise buildings. Here the need for quality control of geometry in real time by engineering geodesists is obvious, since the building is exposed to external influences like wind and temperature.
Quality Model
Again the quality model developed is process- and product-related and it considers characteristics and parameters. The parameters are chosen to fulfill the requirements given or expected by the construction engineers or the principal. The table gives an overview on the characteristics and parameters defined within EQUIP.
Table 2: Quality characteristics and parameters for engineering geodesy processes
(Schweitzer & Schwieger 2011)
Requirements Parameters Characteristics
Compliance with the tolerance and the absolute position in space - Standard deviation (measure) Accuracy
- Tolerance correctness (measure)
Adherence to the topological relation between the elements - Topological correctness (indicator) Correctness
Completeness of the elements in houses construction - Number of missing elements (count) - Number of odd elements (count) Completeness
Completeness of the measurement processes - Adherence to the plan (rate)
Reliability of the measurement processes and measuring equipment - Condition density (rate) - Minimal detectable error (measure) - Vulnerability to failures (rate) Reliability
Adherence to timescale - Time Delay (rate) Timeliness
From the primary requirements „Compliance with the size tolerance and the absolute position in space”, two parameters can be derived, the standard deviation which is structured by the characteristic “Accuracy”, and the tolerance correctness, structured by “Correctness”. In the following the characteristics are explained in detail. Since the definitions are application oriented they differ slightly
- Accuracy: Degree of adherence of the measured value to the true or expected value
- Correctness: Degree of adherence of measurement processes or elements to the planned processes or elements
- Completeness: Degree of adherence of the entire elements or processes regarding to the solid geometry
- Reliability: Probability to avoid or detect errors and failures within a process or an evaluation
- Timeliness: Adherence to the time schedule
Unlike the quality model for residential houses (last chapter), where the distinction between product and process quality is realized on the characteristic level (product- and process-oriented characteristics), here it is realized on parameter level. The parameters “Adherence to the plan”, “Vulnerability to failures” and “Time Delay” are exclusive process-oriented parameters and the others are first and
foremost product-oriented. In any case, a product parameter can also be derived to rate a process. This is the case, if the product is the result of one sub-process only. For the description of parameters like standard deviation or condition density it is referred to Schweitzer & Schwieger (2011). The only parameter described in more detail in this section is the “tolerance correctness”.
A tolerance T of a building component is met, if the actual deviation which is the difference between the actual size and the nominal size, is smaller than the limit deviation= T/2 (see Fig. 6). This can be expressed with the following equation:
T
- > actaul deviation = | actual size — nominal size | (10)
To check the compliance of the tolerance of a building component, the actual size has to be measured with a measuring device.
In equation 10 (see also Fig. 6) the measured value of the actual size is assumed as error-free. In reality the errors of the measuring device which measures the actual size have to be considered. The measured size of a building component is indicated as Smeas. The difference between Smeas and the actual size is caused by the uncertainty of the measuring device. This issue is shown in Fig. 6.
<----------------------------------------►
Figure 6: Use of terms in the field of building tolerances (translated and modified from (DIN, 2005))
To consider this, the standard deviation of the measuring device has to be converted into the surveying tolerance T'M which is charged with the tolerance T. So the surveying tolerance T'M of the instrument or the measurement has to be subtracted of the nominal tolerance T taken e.g. from DIN 18202. The surveying tolerance T'M and the Tolerance T do not depend on each other. Following the quadratic tolerance propagation law (Ertl, 2006) equation 10 has to be enhanced to
iJt2 - T'u > \Smeas - nominal size |. (11)
The tolerance correctness Tk is consequently an aggregated value that delivers a statement of compliance with the required tolerance. If the tolerance correctness Tk is
greater than zero or equal to zero, the tolerance is met. If Tk is negative, the tolerance is missed:
Tk = - T^ - ISmeas - nominal size| (12)
- Smeas: measured value
- T: tolerance taken e.g. from standard DIN 18202
- T’M: computed surveying tolerance of a measurement device or measurement with a specific accuracy level о.
Process Model
Within this research project the quality should be propagated through the engineering geodesy process in a mathematically strict way. One possibility to do this, are artificial neuronal networks (e.g. Laufer 2011). Here, another approach is followed: the process is modeled using Petri-Nets (Peterson 1981). Petri-Nets are very useful to model parallel processes and time restrictions. The approach is applied in several scientific disciplines. A Petri-Net is composed of four components: places, transitions, edges and tokens. Places model the passive components of a process. Places have the possibility to store tokens and they have a capacity indicating how many tokens can be stored. Places are represented as circles. Transitions are the active components of a process. A transition will transport tokens, if it is activated. The transitions are represented as rectangles. The tokens represent the actors (e.g. staff to perform measurements) or materials needed for a process. Finally, the edges connect places and transitions. They may have restrictions, e.g. that only two tokens are allowed to be transported at the same time. For further details the authors refer to Berkhahn et al. (2010). Fig. 7 shows a simplified example for the self-climbing formwork.
preparation of the measurement stationing stake out
measuring process prepared instrument prepared
preparation of the formwork alignment of the another alignment
formwork prepared formwork necessary
Figure 7: Modeling the alignment of a formwork element by Petri-Nets (translated
from Berkhahn et al. 2010)
Based on Petri-Nets, efficiency optimization (Rehr et al. 2011) and quality propagation are realized. Both techniques are included in the Petri-Net model, but they work independently.
Quality Propagation
In contradiction to the approach described in chapter 3, the parameters will be propagated through the process in a mathematically correct way. For geodesists the
variance or the standard deviation is the mostly used quality parameter. If the process relies on vectorial input, covariance matrices have to be propagated through the process. This may be carried through by the propagation law of variances (propagation of errors) (e.g. Niemeier 2002) or the Monte Carlo simulation (e.g. Binder 1979). Since the second variant avoids the problem of non-linear relationships and therefore may be used for any application, the authors decide to adapt the Monte Carlo method. Currently, a software tool is developed that fulfills the needs for quality assurance during the engineering geodesy process, because it can predict future results on simulation base. Fig. 8 shows a screenshot of the new tool for the example process of free stationing. For the time being the software tool is in German language at has a basic MMI. The position of the free station (black dot) and the control points (circles) can be chosen interactively and without restrictions. The resulting standard deviations are Monte Carlo generated on the base of different simulated input data like distances, anlges or coordinates. The standard deviation in x-, y- and z-direction are given in meters behind the word “Genauigkeit”. Further information, e.g. the covariance matrix is provided in text-files.
The other quality parameters described in table 2 are propagated, too. For further details the authors refer to EQUIP (2010).
Figure 8: Quality propagation tool; exemplary screenshot for free stationing
SUMMARY AND OUTLOOK
This paper summarizes the results of two research projects dealing with quality models, process models and quality propagation in the construction domain. Some of
the differences between the two projects are based on the orientation of the funding agencies. QuCon is application-oriented and should directly serve SMEs for their daily work. In contradiction EQUIP should deliver fundamental and interdisciplinary research results to prepare future applications at the borderline of engineering geodesy and construction engineering. These different orientations are the main reason for the divergent characteristics. The following table will summarize these differences which were already depicted in the respective chapters. It is very important to mention that the simplified models of the QuCon project deliver the possibility to determine one total quality parameter. This is not possible up to now for the parameter-based EQUIP case.
The project QuCon is already finalized. For the future the acceptance of the QuCon software within construction management has to be evaluated. The project partners have to learn about the suitability of the software for SMEs. It may be possible that adoptions and changes of the software as well as the underlying mathematical model have to be realized in the future.
Table 3: Comparison of the characteristics for the two presented approaches
Characteristic QuCon EQUIP
Research Orientation Application oriented Fundamental research
Application Complete construction process Engineering geodesy processes
Quality Model Characteristic based Parameter based
Process Model Visual, e.g. Gantt charts Mathematical, Petri-Nets
Quality Propagation Weighted Average Process related, e.g. Monte Carlo
Total Quality Index yes no
Regarding EQUIP, the quality propagation methods have to be further developed and integrated into the software tool. Finally, the efficiency optimization and the quality propagation should be integrated in one software tool and into the Petri-Net based process model.
A long-term aim for quality modeling and processing should be a parameter-based interdisciplinary quality model that includes a realistic process model and a parameter-based and process-related quality propagation leading to a total quality index. But this is really a vision for the time being.
ACKNOWLEDGEMENT
The investigations published in this article are granted by the AIF (German Federation of Industrial Research Associations) and the DFG (German Research Foundation) under the signs AIF No 14 EN/1 and SCHW 838/3. Therefore, the authors cordially thank the funding agencies.
REMARK
This article is a summary of the following references: Berkhahn et al. (2010), Schweitzer & Schwieger (2011), Schwieger et al. (2010) and Zhang & Schwieger (2011).
REFERENCES
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BIOGRAPHICAL NOTES
Prof. Dr.-Ing. habil. Volker Schwieger
1983 - 1989 Studies of Geodesy in Hannover 1989 Dipl.-Ing. in Geodesy (University of Hannover)
1998 Dr.-Ing. in Geodesy (University of Hannover)
2003 Head of Department “Metrology” at the Institute for Applications of Geodesy to
Engineering, University of Stuttgart
2004 Habilitation (University of Stuttgart)
2010 Professor, Head of Institute for Applications of Geodesy to Engineering, University of Stuttgart
2010 Renaming the Institute to Institute of Engineering Geodesy, University of Stuttgart (IIGS)
Dipl.-Ing. Li Zhang
2002 - 2003 Studies of Geodesy in China (University of Wuhan)
2004 - 2009 Studies of Geodesy in Germany (University of Stuttgart)
2009 Dipl.-Ing. in Geodesy (University of Stuttgart)
2009 - Scientific Associate at Institute of Engineering Geodesy,
University of Stuttgart
Dipl.-Ing. Jurgen Schweitzer
2003-2008 Studies of Geodesy in Karlsruhe (Germany)
2008 Dipl.-Ing. in Geodesy (University of Karlsruhe)
2008 - Scientific Associate at Institute of Engineering Geodesy,
University of Stuttgart
CONTACTS
Prof. Dr.-Ing. habil. Volker Schwieger / Dipl.-Ing. Li Zhang / Dipl.-Ing. Jurgen Schweitzer
University of Stuttgart
Institute of Engineering Geodesy (IIGS)
Geschwister-Scholl-Str. 24 D D-70174 Stuttgart GERMANY
Tel. + 49/711-685-84040 | -84049 | -84065 Fax + 49/711-685-84044
Email: [email protected] / [email protected] /
Web site: http://www.uni-stuttgart.de/ingeo/
© V Schwieger, Li Zhang, Jurgen Schweitzer, 2011
