- Email: [email protected]
Simulating group work in mechanical engineering design departments
Symbiosis of Human and Artifact Y. Anzai, K. Ogawa and H. Mori (Editors) 1995 Elsevier Science B.V.
775
Simulating group work in mechanical engineering design departments Friedhelm STEIDEL Chair of Ergonomics and Industrial Engineering, Faculty of Electrical and Mechanical Engineering, Brandenburg Technical University of Cottbus, Postbox 10 13 44, D-03013 Cottbus, Germany
1
Introduction
Technical changes like the introduction of CA-techniques are an opportunity to change work organization. However, in general, the introduction of CAtechniques does not go hand in hand with such a restructuring. Empirical case studies in mechanical design departments showed the following problems: the staff was not well qualified to use CAD-systems, CAD was used as an electronic drawing board and the work organization within the design departments had not changed at all. Neither was there a change towards cooperation with other departments like the production planning department [1,2,3]. A lack of efficiency and a suboptimal task distribution to individuals were results of this kind of CAD practice. No positive impact on the length of the run of these projects was achieved.
Modeling design departments In this situation a simulation model was developed in order to predict the effects of organizational changes[4]. With this model, it is possible to simulate cooperative design work. The design process is modeled following the phase models of design methodology[5], that means as a highly iterative process, and it takes into account the necessary cooperation of a group of staff that works together on one project. Labor division is modeled in two dimensions - one where design projects are divided into several subsystems and one where different parts of the design process are executed by different persons. A new, staff oriented simulation approach also allows to describe staff by different dimensions of qualification e.g. qualification for design tasks or qualification for using CA-tools. The work organization is described by a cooperation network of staff, by the staffs responsibility for design phases and types of design projects and by rules that predict how the labor division inherent in a design project is used. During a simulation run, a sample of different design tasks is generated. The simulation output data is recorded after the system has reached stationary state. The output data consists in a detailed diary of the simulated persons in which every action and state of the person is marked (like e.g. a person treating a design task in a specified state, having communication partners, using CA-tools). This diary is evaluated to obtain characteristic output data which represents information on
776 the system under aspects of working" conditions for each indivdual and the system's performance.
3
Validation
of the model
The simulation model has been validated by using input data obtained in case studies and by comparing the simulation output with the real system's behavior. The data collected in empirical studies describes the input of the design model like types and frequency of design tasks, work organization and staff quantity and qualification. Equivalent to t h e s i m u l a t i o n output a very detailed diary of the design staffs activity was written by the help of a computer based questionnaire[3]. This diary contains answers which describe the following aspects of the design work: -
-
activities in design phases, activities concerning individual design tasks or additional tasks, the use of tools like a CAD-System, phone, catalogues and contact with persons inside and outside the department.
What is presented here is a comparison between some results of a simulation run and some of an empirical study of a small design department consisting of 3 design engineers and 3 draftspersons (Figure 1). The comparison of the fields of activities and the use of CAD fits quite well. Nevertheless there are differences in the times of cooperation of the staff in the real world and the simulation. This may be explained by a lack in simulating informal processes. This effect is mostly visible at the border of the fields of activity between engineers and draftspersons. In the real world the engineers used to perform a small but communication intensive part of the detailed design. This informal activity is not represented by the simulation model where simulated persons follow the formal rules strictly.
4
Simulation
experiment
The simulation model was used to carry out a simulation experiment. The aim of this experiment was to find rules for the organizational design of work in CADusing design departments. Tasks of production planning were included in a sixphase design process model to evaluate also new organizational models like simultaneous engineering or integrated project teams for design and production planning. The simulated department had a size of 24 persons, among which were designers, draftspersons and production planners. During the experiment the input of the simulation model was systematically varied in four dimensions, which describe: -
the size of work groups, the width of the staffs responsibility and qualification for tasks in the design process (variation from two to four design phases), the synchronization of parallelly treated subtasks (to simulate department borders and a formal organization) and the degree of CAD-application during the design process.
777
Tasks executed
~
Conceptual
Designers
pesi.gn.
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Embodiment Design Detail Design i Tasks not related to design projects
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empirical data simulation output
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40
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0 20 40 60 80 in % of total working time
40
60 8-0 10b in % of design task proceeding time
Time u s i n g CAD
Designers Draftspersons
0
20
N e e d of c o o p e r a t i o n
Designers
0
10
Draftspersons
20 0 10 20 in % of design task proceeding time
Figure. 1. Comparison of results of empirical study and of a simulation run Furthermore the different mixtures of design tasks were generated and used as input of the simulation system. This aims to obtain information on the question whether the results of the experiment may be used in general or whether they have to be specified for certain structures of design tasks. Design task describing parameters were the overall volume, the frequency of incoming tasks, the distribution of work on design phases (new design vs. adaptive design) and the task's complexity described by the ratio of a predicted total amount of iterative work to the work in a first cycle of the design process. The total amount of incoming workload within a time period was maintained at the same level during the experiment. Typical output variables of the simulation experiment on the employee level are the individual work load, the degree of specialization for types of design tasks or subtasks. Another important output variable is the quantity and the quality of
778 contact with other staff for information exchange as well as the possibility of autonomous work planning. On the department level, the following categories are taken: the flexibility of the system's response to internal and external disturbances, performance describing data like queues and the length of the run of different design projects. A direction of optimization was given for each output variable. For both levels, a summary variable was determined by taking the mean of the z-transformed individual variables, which indicate a.) the performance of the whole department and b.) the work situation of individuals. Some of the effects on these variables observed in more than 5000 simulation runs are discussed here (68 design task structures x 81 states of organization and qualification). The effects of the structure of design tasks on the summary variables is shown in Figure 2. The most important one is given by the total amount of work individual design tasks represent. That means, that 'bigger' design tasks produce less 'friction' in the system. The novelty and the complexity of design tasks have only little effect on the output.
summary
su~ry 1 variable
01 ~ variable ~
1,4 1,6 1,8 Complexity
-
summary 1
100 200 300 400 total volume in working hours
-4- on the performance level --- on the personal level
itvariable 1
-1
'
'
2,3 2,5 2,7 maximum of volume distribution on design phase no.
Figure 2. Effect of design task describing data on condensed output variables The only effect of the design task describing input variables is seen on the level of the output variables. This was shown by an analysis of variance in which there were no significant combined effects of input data describing design tasks and Of input data describing organization and qualification. That means, that rules for the organizational design can be given independently from the structure of incoming design tasks. Even if a simulation model is not able to show all positive effects of informal communication and cooperation in group work, the quantitative results of the simulation experiment allow to identify forms of work organization in design departments for which the output variables on the staff level and on the performance level of the department are optimized complementarily.
779
Characteristic features of the optimal forms of work organization are -
a broad qualification and responsibility of the staff along the design process, a limited qualification and responsibility concerning different types of design projects, a limited n u m b e r of persons working together in a group (less than 12 persons) and lifting formal barriers between the mechanical design d e p a r t m e n t and the production planning department.
One has to take into account t h a t organizational design can only have positive effects if all the above mentioned conditions are fulfilled simultaneously. The most i m p o r t a n t effect of singular intervention was received by broadening the staffs qualification along the design process. This effect is shown in Figure 3.
sunnnary variable (Q. f. Ph. = 2/6) 1]
sun~nary variable (Q. f. Ph. = 3/6)) 1!
0
summary variable (Q. f. Ph. = 4/6) 1 0
-1
6 12 24 No. of persons per group
4-
-1
on the performance level
--*- on the personal level
'
6 12 24 No. of persons per group
-1
6 12 24 No. of persons per group
Q. f. Ph.: Qualification for phases along the design process. The design process in the experiment has 6 phases.
Figure 3. Effect of broadening the staffs qualification along the design process on condensed output variables. CAD-application in the design process was a s s u m e d to accelerate the individual's work. Despite this assumption, the variation of the degree of CAD-application alone had very little effect on the performance describing data (e.g. the length of the run of design projects). The most i m p o r t a n t effect of broadening CADapplication was to limit the workload to individuals. Due to the internal organizational friction, this effect could not be transformed into accelerating design projects on the d e p a r t m e n t level (Figure 4). 5
Conclusion
The method of modeling and simulation gives insights into the behavior of complex systems. Under the conditions a s s u m e d in the simulation model, measures of organizational design were found to have a much more important
780 impact on the work situation of each individual and on the performance of the whole department than the introduction of new techniques.
-
summary variable (CAD-Appl.=I) 1
summary variable (CAD-Appl.=2) 1
i
o .,-
6 12 24 No. of persons per group
-1
6 12 24 No. of persons per group
summary variable (CAD-Appl.= 3) 1
o -
6 12 24 No. of persons per group
-'-on the performance level CAD-Appl.: Type of CAD-Application during --*-on the personal level the design process: Type 1: CAD is used in 3 of 6 phases Type 2: CAD is used in 4 of 6 phases Type 3: CAD is used in 5 of 6 phases Figure 4. Effect of broadening CAD-application along the design process in case of a broad qualification of the staff along the design process (Width of Qualification = 4/6). R e f e r e n c e s
1. Reuschenbach, Th.; Steidel, F.: Structuring the design process in CAD-using design departments. In: Luczak, H.; ~akir, A.E.; ~akir, G.(Eds.): Work With Display Units. Abstractbook of the Third International Scientific Conference on Work with Display Units. September 1 - 4, 1992, p. H-11. 2. Muhlbradt, T.; Riickert, C.; Springer, J.; Beitz, W.; Luczak, H.: Analysis of stress and strain of design engineers solving mechanical problems Integrating a comparison of conventional and Computer-Aided Design-work into the development of a design Management System. In: Proceedings of the 12th Triennial Congress of the International Ergonomics Association, Volume 5. pp. 358-360 3. Steidel, F.: Modellierung arbeitsteilig ausgefiihrter, rechnerunterstiitzter Konstruktionsarbeit - MSglichkeiten und Grenzen personenzentrierter Simulation. Dissertation TU Berlin 1993. 4. Steidel, F.; Reuschenbach, Th.; Luczak, H.: Simulation of an Organization in CAD Using Design Departments. In: Noro, K.; Brown, O. (Eds.): Human Factors in Organizational Design and Management - III. Proc.: Third International Symposium on Human Factors in Organizational Design and Management. Amsterdam New York: North Holland 1990, pp. 359-362. 5. Pahl, G.; Beitz, W.(1984): Engineering design. London: Design Council 1984.
775
Simulating group work in mechanical engineering design departments Friedhelm STEIDEL Chair of Ergonomics and Industrial Engineering, Faculty of Electrical and Mechanical Engineering, Brandenburg Technical University of Cottbus, Postbox 10 13 44, D-03013 Cottbus, Germany
1
Introduction
Technical changes like the introduction of CA-techniques are an opportunity to change work organization. However, in general, the introduction of CAtechniques does not go hand in hand with such a restructuring. Empirical case studies in mechanical design departments showed the following problems: the staff was not well qualified to use CAD-systems, CAD was used as an electronic drawing board and the work organization within the design departments had not changed at all. Neither was there a change towards cooperation with other departments like the production planning department [1,2,3]. A lack of efficiency and a suboptimal task distribution to individuals were results of this kind of CAD practice. No positive impact on the length of the run of these projects was achieved.
Modeling design departments In this situation a simulation model was developed in order to predict the effects of organizational changes[4]. With this model, it is possible to simulate cooperative design work. The design process is modeled following the phase models of design methodology[5], that means as a highly iterative process, and it takes into account the necessary cooperation of a group of staff that works together on one project. Labor division is modeled in two dimensions - one where design projects are divided into several subsystems and one where different parts of the design process are executed by different persons. A new, staff oriented simulation approach also allows to describe staff by different dimensions of qualification e.g. qualification for design tasks or qualification for using CA-tools. The work organization is described by a cooperation network of staff, by the staffs responsibility for design phases and types of design projects and by rules that predict how the labor division inherent in a design project is used. During a simulation run, a sample of different design tasks is generated. The simulation output data is recorded after the system has reached stationary state. The output data consists in a detailed diary of the simulated persons in which every action and state of the person is marked (like e.g. a person treating a design task in a specified state, having communication partners, using CA-tools). This diary is evaluated to obtain characteristic output data which represents information on
776 the system under aspects of working" conditions for each indivdual and the system's performance.
3
Validation
of the model
The simulation model has been validated by using input data obtained in case studies and by comparing the simulation output with the real system's behavior. The data collected in empirical studies describes the input of the design model like types and frequency of design tasks, work organization and staff quantity and qualification. Equivalent to t h e s i m u l a t i o n output a very detailed diary of the design staffs activity was written by the help of a computer based questionnaire[3]. This diary contains answers which describe the following aspects of the design work: -
-
activities in design phases, activities concerning individual design tasks or additional tasks, the use of tools like a CAD-System, phone, catalogues and contact with persons inside and outside the department.
What is presented here is a comparison between some results of a simulation run and some of an empirical study of a small design department consisting of 3 design engineers and 3 draftspersons (Figure 1). The comparison of the fields of activities and the use of CAD fits quite well. Nevertheless there are differences in the times of cooperation of the staff in the real world and the simulation. This may be explained by a lack in simulating informal processes. This effect is mostly visible at the border of the fields of activity between engineers and draftspersons. In the real world the engineers used to perform a small but communication intensive part of the detailed design. This informal activity is not represented by the simulation model where simulated persons follow the formal rules strictly.
4
Simulation
experiment
The simulation model was used to carry out a simulation experiment. The aim of this experiment was to find rules for the organizational design of work in CADusing design departments. Tasks of production planning were included in a sixphase design process model to evaluate also new organizational models like simultaneous engineering or integrated project teams for design and production planning. The simulated department had a size of 24 persons, among which were designers, draftspersons and production planners. During the experiment the input of the simulation model was systematically varied in four dimensions, which describe: -
the size of work groups, the width of the staffs responsibility and qualification for tasks in the design process (variation from two to four design phases), the synchronization of parallelly treated subtasks (to simulate department borders and a formal organization) and the degree of CAD-application during the design process.
777
Tasks executed
~
Conceptual
Designers
pesi.gn.
.
Embodiment Design Detail Design i Tasks not related to design projects
.
.
.
.
.
.
.
.
.
empirical data simulation output
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40
60
0 20 40 60 80 in % of total working time
40
60 8-0 10b in % of design task proceeding time
Time u s i n g CAD
Designers Draftspersons
0
20
N e e d of c o o p e r a t i o n
Designers
0
10
Draftspersons
20 0 10 20 in % of design task proceeding time
Figure. 1. Comparison of results of empirical study and of a simulation run Furthermore the different mixtures of design tasks were generated and used as input of the simulation system. This aims to obtain information on the question whether the results of the experiment may be used in general or whether they have to be specified for certain structures of design tasks. Design task describing parameters were the overall volume, the frequency of incoming tasks, the distribution of work on design phases (new design vs. adaptive design) and the task's complexity described by the ratio of a predicted total amount of iterative work to the work in a first cycle of the design process. The total amount of incoming workload within a time period was maintained at the same level during the experiment. Typical output variables of the simulation experiment on the employee level are the individual work load, the degree of specialization for types of design tasks or subtasks. Another important output variable is the quantity and the quality of
778 contact with other staff for information exchange as well as the possibility of autonomous work planning. On the department level, the following categories are taken: the flexibility of the system's response to internal and external disturbances, performance describing data like queues and the length of the run of different design projects. A direction of optimization was given for each output variable. For both levels, a summary variable was determined by taking the mean of the z-transformed individual variables, which indicate a.) the performance of the whole department and b.) the work situation of individuals. Some of the effects on these variables observed in more than 5000 simulation runs are discussed here (68 design task structures x 81 states of organization and qualification). The effects of the structure of design tasks on the summary variables is shown in Figure 2. The most important one is given by the total amount of work individual design tasks represent. That means, that 'bigger' design tasks produce less 'friction' in the system. The novelty and the complexity of design tasks have only little effect on the output.
summary
su~ry 1 variable
01 ~ variable ~
1,4 1,6 1,8 Complexity
-
summary 1
100 200 300 400 total volume in working hours
-4- on the performance level --- on the personal level
itvariable 1
-1
'
'
2,3 2,5 2,7 maximum of volume distribution on design phase no.
Figure 2. Effect of design task describing data on condensed output variables The only effect of the design task describing input variables is seen on the level of the output variables. This was shown by an analysis of variance in which there were no significant combined effects of input data describing design tasks and Of input data describing organization and qualification. That means, that rules for the organizational design can be given independently from the structure of incoming design tasks. Even if a simulation model is not able to show all positive effects of informal communication and cooperation in group work, the quantitative results of the simulation experiment allow to identify forms of work organization in design departments for which the output variables on the staff level and on the performance level of the department are optimized complementarily.
779
Characteristic features of the optimal forms of work organization are -
a broad qualification and responsibility of the staff along the design process, a limited qualification and responsibility concerning different types of design projects, a limited n u m b e r of persons working together in a group (less than 12 persons) and lifting formal barriers between the mechanical design d e p a r t m e n t and the production planning department.
One has to take into account t h a t organizational design can only have positive effects if all the above mentioned conditions are fulfilled simultaneously. The most i m p o r t a n t effect of singular intervention was received by broadening the staffs qualification along the design process. This effect is shown in Figure 3.
sunnnary variable (Q. f. Ph. = 2/6) 1]
sun~nary variable (Q. f. Ph. = 3/6)) 1!
0
summary variable (Q. f. Ph. = 4/6) 1 0
-1
6 12 24 No. of persons per group
4-
-1
on the performance level
--*- on the personal level
'
6 12 24 No. of persons per group
-1
6 12 24 No. of persons per group
Q. f. Ph.: Qualification for phases along the design process. The design process in the experiment has 6 phases.
Figure 3. Effect of broadening the staffs qualification along the design process on condensed output variables. CAD-application in the design process was a s s u m e d to accelerate the individual's work. Despite this assumption, the variation of the degree of CAD-application alone had very little effect on the performance describing data (e.g. the length of the run of design projects). The most i m p o r t a n t effect of broadening CADapplication was to limit the workload to individuals. Due to the internal organizational friction, this effect could not be transformed into accelerating design projects on the d e p a r t m e n t level (Figure 4). 5
Conclusion
The method of modeling and simulation gives insights into the behavior of complex systems. Under the conditions a s s u m e d in the simulation model, measures of organizational design were found to have a much more important
780 impact on the work situation of each individual and on the performance of the whole department than the introduction of new techniques.
-
summary variable (CAD-Appl.=I) 1
summary variable (CAD-Appl.=2) 1
i
o .,-
6 12 24 No. of persons per group
-1
6 12 24 No. of persons per group
summary variable (CAD-Appl.= 3) 1
o -
6 12 24 No. of persons per group
-'-on the performance level CAD-Appl.: Type of CAD-Application during --*-on the personal level the design process: Type 1: CAD is used in 3 of 6 phases Type 2: CAD is used in 4 of 6 phases Type 3: CAD is used in 5 of 6 phases Figure 4. Effect of broadening CAD-application along the design process in case of a broad qualification of the staff along the design process (Width of Qualification = 4/6). R e f e r e n c e s
1. Reuschenbach, Th.; Steidel, F.: Structuring the design process in CAD-using design departments. In: Luczak, H.; ~akir, A.E.; ~akir, G.(Eds.): Work With Display Units. Abstractbook of the Third International Scientific Conference on Work with Display Units. September 1 - 4, 1992, p. H-11. 2. Muhlbradt, T.; Riickert, C.; Springer, J.; Beitz, W.; Luczak, H.: Analysis of stress and strain of design engineers solving mechanical problems Integrating a comparison of conventional and Computer-Aided Design-work into the development of a design Management System. In: Proceedings of the 12th Triennial Congress of the International Ergonomics Association, Volume 5. pp. 358-360 3. Steidel, F.: Modellierung arbeitsteilig ausgefiihrter, rechnerunterstiitzter Konstruktionsarbeit - MSglichkeiten und Grenzen personenzentrierter Simulation. Dissertation TU Berlin 1993. 4. Steidel, F.; Reuschenbach, Th.; Luczak, H.: Simulation of an Organization in CAD Using Design Departments. In: Noro, K.; Brown, O. (Eds.): Human Factors in Organizational Design and Management - III. Proc.: Third International Symposium on Human Factors in Organizational Design and Management. Amsterdam New York: North Holland 1990, pp. 359-362. 5. Pahl, G.; Beitz, W.(1984): Engineering design. London: Design Council 1984.