=Paper= {{Paper |id=Vol-3659/IJCKG_2023_D3 |storemode=property |title=An Application of Functional Decomposition Tree Technology to Collaborative Robot Introduction Manual for Non-Experts |pdfUrl=https://ceur-ws.org/Vol-3659/IJCKG_2023_D3.pdf |volume=Vol-3659 |authors=Aoi Hiraoka,Tomohiko Yamaguchi,Munehiko Sasajima |dblpUrl=https://dblp.org/rec/conf/jist/HiraokaYS23 }} ==An Application of Functional Decomposition Tree Technology to Collaborative Robot Introduction Manual for Non-Experts== https://ceur-ws.org/Vol-3659/IJCKG_2023_D3.pdf
                                An Application of Functional Decomposition Tree
                                Technology to Collaborative Robot Introduction
                                Manual for Non-Experts
                                Aoi Hiraoka1 , Tomohiko Yamaguchi2 and Munehiko Sasajima1
                                1
                                    University of Hyogo , 8-2-1, Gakuennishimachi, Nishi-ku, Kobe-shi, Hyogo, 651-2103, Japan
                                1
                                    iCOM Robotics Inc. , 811-1, Shikiji-cho, Ono-shi, Hyogo, 675-1367, Japan


                                                                         Abstract
                                                                         In order to reduce the cost of introducing collaborative robots, the authors are studying tablet-type
                                                                         electronic manuals using functional decomposition tree technology that enable non-experts (robot users)
                                                                         to introduce robots by themselves. Since the creation of such manuals is time-consuming, a methodology
                                                                         that enables experts (robot manufacturers) to create manuals for non-experts themselves is needed
                                                                         to promote the widespread use of collaborative robots, instead of knowledge engineers continuously
                                                                         creating manuals for each individual robot.

                                                                         Keywords
                                                                         collaborative robot, functional decomposition tree, manual,




                                1. Introduction
                                The purpose of this study is to establish a methodology for creating electronic manuals for
                                non-experts, and to create guidelines for their construction, using the introduction manual of
                                collaborative robots as a motif.
                                   One of the solutions to labor shortages in the manufacturing industry is the introduction of
                                collaborative robots, but the high cost of introducing such robots has prevented their widespread
                                use. The authors have paid attention to the installation costs incurred by experts (robot manu-
                                facturers), and believe that if non-experts (robot users) could take charge of the installation work
                                themselves, the robot installation costs paid to experts would be reduced. We have developed a
                                manual for non-experts by decomposing a manual for experts into detailed procedures using
                                a functional decomposition tree [1] for a part of the installation of a collaborative robot, and
                                conducted evaluation experiments [2].
                                   On the other hand, the preparation of such manuals for non-experts it is costly. In fact, when
                                the authors created a manual for non-experts for the Palletizer X collaborative robot, it took
                                more than one year just to create a text-based functional decomposition style manual, and
                                more than 100 hours to create video contents to supplement the text explanations until the
                                manual could be created so that only non-experts could go through the work. In order to make

                                IJCKG 2023 Poster and Demo track
                                $ ad23i059@guh.u-hyogo.ac.jp (A. Hiraoka); yamaguchi@icom-giken.com (T. Yamaguchi);
                                sasajima@sis.u-hyogo.ac.jp (M. Sasajima)
                                                                       © 2023 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
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Figure 1: Diagram of a functional decomposition tree in the form of a manual (in Japanese)


manuals for non-experts practical, the cost of the creation process itself must also be reduced.
For example, a methodology that enables experts themselves to create manuals for non-experts
is needed. Previous studies, for example, Sannami [3], investigate how to present a manual,
not on the elements that should be included in a manual. As far as the author has been able to
ascertain, there are no studies on manual creation methodologies that satisfy our needs.
   Therefore, in this study, we examined the elements necessary for creating manuals for non-
experts to enable experts to create manuals that allow non-experts to take the initiative in
implementing collaborative robotics.


2. Electronic manuals for non-experts
The manual handled in this study is a manual that is created by structuring the introduction
workflow using a functional decomposition tree and converting it into a manual form (Figure1).
Functional decomposition refers to the development of a desired function into a sequence of
sub-functions that can achieve it [1], which is expressed in the form of a tree, called a functional
decomposition tree. The manual also includes links to complementary videos that supplement
the textual explanations.


3. Manual Evaluation Experiments and Results
A total of five manual evaluation experiments were conducted with non-experts as subjects, in
which they performed a part of the installation work of a collaborative robot using an electronic
manual that had been created. In each experiment, the experimental conditions were slightly
changed, and the effects of these changes on the subjects performance were compared and
categorized.
   Outline of the experiment is as following. Palletizer X is a collaborative robot that performs
palletizing, which is the stacking of packages on pallets that flow from a conveyor. Subjects were
asked to perform three main tasks in the installation of Palletizer X, using an electronic manual
as a reference. The subjects for each experiment were two people with no prior knowledge
of collaborative robots. Subject interviews were conducted after each experiment. In each
Figure 2: Comparison of complementary videos for "Conducting Teaching" (in Japanese)


experiment, we analyzed the changes that affected the success of the task with reference to the
results of the previous experiment, and generalized and categorized them.
   Then we describe experimental results here. The authors used the manual for non-experts in
the first experiment, but the subjects failed to complete the task. But by improving the manual
step by step for each experiment, the success rate eventually rose to 89% to 100%. Therefore,
it was found that even non-experts can take charge of the introduction work by using the
introduction work manual [2].
   In addition, from the changes made to the experimental conditions in each experiment,
the changes that affected the success of the work were found and categorized. One of the
classifications, "multidimensional expression," is described below.
   One of the tasks, "conduct teaching", for example, the robot arm is operated using an attached
touch panel to set the coordinate axes of the collaborative robot at the time of shipment in the
direction of the actual coordinate axes at the actual site, and the tip of an instrument attached
to the arm called "jig" must be aligned with the four points specified on a board called "pallet"
within an error margin of a few mm. In the complementary movie of the first experiment (left
side of Figure2), the robot was too close to the object, making it difficult to understand the
positional relationship between the robot and the operator and the final state of the tip of the
jig. As a result, the instructions were not well communicated to the subject, and the work could
not be performed within the allowable error. Therefore, in the second supplemental video (right
side of Figure2), we attempted a multifaceted expression by re-editing the video to include a
bird’s-eye view of the entire robot from above, a video showing the robot itself and the operator,
and multiple viewpoints of the final state of the jig. This improved the accuracy of the work
and allowed teaching to be performed at the correct position.
   Some of the changes were effective in making the work more successful, as in the categories
presented above, while others were not. In this study, the changes that were effective were the
study focused on the changes that were effective, and divided them into eight categories.


4. Draft Guidelines for Manual Construction
A guideline was developed for the experts, not the knowledge engineers, to make them being
able to make such manuals we have proposed in this paper by themselves.
Draft guidelines for the construction of a manual for non-experts:
   1. The manual is to be prototyped several times using functional decomposition trees: the first time to avoid
      hazards, the second time to solve functional problems, and the third and later times to add words that are
      difficult to understand, etc. Further improvements should be made by conducting multiple experiments on
      the use of the manual by test subjects.
   2. Be sure to write about procedures for worker safety and any terms that have different definitions for experts
      and non-experts.
   3. The peripheral knowledge required for assembly, such as names of parts and basic work procedures, should
      be included in the manual or documents to be included with the manual.
   4. For the procedures that the subjects were unsure of in the initial experiments, the instructions should be less
      granular and more specific.
   5. For procedures for which the subjects do not understand the reason for the work in the initial experiments,
      the manual will indicate the failures that would result if the procedure were not performed.
   6. For critical tasks that determine the accuracy of the entire operation, the manual’s instructions should be
      multifaceted.
   7. We will also try to describe procedures that make the work easier to perform.
   8. If it is expected to facilitate assembly, instructions for manual peripherals are also provided.
   9. If initial experiments reveal issues such as the manual being difficult to see or read, consider the possibility
      of changing the interface of the manual itself.
  10. The field manual is not always correct. When errors in the field manuals are discovered through repeated
      experiments, the manuals themselves are revised and feedback is provided to the field.


5. Conclusion
In this study, we examined a methodology to enable experts themselves to create manuals
that enable non-experts to take on the task of introducing collaborative robots. The guideline
proposed in this paper is based on a single model of the Palletizer X, and is not a general one.
In order to generalize this guideline to various models, we plan to apply our method for other
collaborative robots, such as different models of palletizers and robots for welding, for example.
We are also planning to conduct experiments in which experts will actually create manuals
using the guidelines we have created. In the future, we would like to make it possible for experts
to take the initiative in creating manuals for non-experts.
Acknowledgments
This research was partially supported by the New Energy and Industrial Technology Develop-
ment Organization (NEDO) JPNP18002.


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