TY - JOUR
T1 - A General Methodology for Adapting Industrial HMIs to Human Operators
AU - Villani, Valeria
AU - Sabattini, Lorenzo
AU - Loch, Frieder
AU - Vogel-Heuser, Birgit
AU - Fantuzzi, Cesare
N1 - Publisher Copyright:
© 2004-2012 IEEE.
PY - 2021/1
Y1 - 2021/1
N2 - Modern production systems are becoming more and more complex to comply with diversified market needs, flexible production, and competitiveness. Despite technological progress, the presence of human operators is still fundamental in production plants, since they have the important role of supervising and monitoring processes, by interacting with such complex machines. The complexity of machines implies an increased complexity of human-machine interfaces (HMIs), which are the main point of contact between the operator and the machine. Thus, HMIs cannot be considered anymore an accessory to the machine and their improvement has become an important part of the design of the whole machines, to enable a nonstressful interaction and make them easy to also use less skilled operators. In this article, we present a general framework for the design of HMIs that adapt to the skills and capabilities of the operator, with the ultimate aim of enabling a smooth and efficient interaction and improving user's situation awareness. Adaptation is achieved by considering three different levels: Perception (i.e., how information is presented), cognition (i.e., what information is presented), and interaction (i.e., how interaction is enabled). For each level, general guidelines for adaptation are provided, thus defining a meta-HMI independent of the application. Finally, some examples of how the proposed adaptation patterns can be applied to the case of procedural and extraordinary maintenance tasks are presented. Note to Practitioners-This article was motivated by the problem of facilitating the interaction of human operators with human-machine interfaces (HMIs) of complex industrial systems. Standard industrial HMIs are static and do not consider the user's characteristics. As a consequence, least-skilled operators are prevented from their use and/or have poor performance. In this article, we suggest a novel methodology to the design of adaptive industrial HMIs that adapt to the skills and capabilities of operators and compensate their limitations (e.g., due to age or inexperience). In particular, we propose a methodological framework that consists of general rules to accommodate the user's characteristics. Adaptation is achieved at three different levels: Perception (i.e., how information is presented), cognition (i.e., what information is presented), and interaction (i.e., how interaction is enabled). The presented rules are independent of the target application. Nevertheless, we establish a relationship between such design rules and user's impairments and capabilities and kind of working tasks. Hence, designers of HMIs are called to instantiate them considering the specific requirements and characteristics of the users and the working tasks of the application at hand.
AB - Modern production systems are becoming more and more complex to comply with diversified market needs, flexible production, and competitiveness. Despite technological progress, the presence of human operators is still fundamental in production plants, since they have the important role of supervising and monitoring processes, by interacting with such complex machines. The complexity of machines implies an increased complexity of human-machine interfaces (HMIs), which are the main point of contact between the operator and the machine. Thus, HMIs cannot be considered anymore an accessory to the machine and their improvement has become an important part of the design of the whole machines, to enable a nonstressful interaction and make them easy to also use less skilled operators. In this article, we present a general framework for the design of HMIs that adapt to the skills and capabilities of the operator, with the ultimate aim of enabling a smooth and efficient interaction and improving user's situation awareness. Adaptation is achieved by considering three different levels: Perception (i.e., how information is presented), cognition (i.e., what information is presented), and interaction (i.e., how interaction is enabled). For each level, general guidelines for adaptation are provided, thus defining a meta-HMI independent of the application. Finally, some examples of how the proposed adaptation patterns can be applied to the case of procedural and extraordinary maintenance tasks are presented. Note to Practitioners-This article was motivated by the problem of facilitating the interaction of human operators with human-machine interfaces (HMIs) of complex industrial systems. Standard industrial HMIs are static and do not consider the user's characteristics. As a consequence, least-skilled operators are prevented from their use and/or have poor performance. In this article, we suggest a novel methodology to the design of adaptive industrial HMIs that adapt to the skills and capabilities of operators and compensate their limitations (e.g., due to age or inexperience). In particular, we propose a methodological framework that consists of general rules to accommodate the user's characteristics. Adaptation is achieved at three different levels: Perception (i.e., how information is presented), cognition (i.e., what information is presented), and interaction (i.e., how interaction is enabled). The presented rules are independent of the target application. Nevertheless, we establish a relationship between such design rules and user's impairments and capabilities and kind of working tasks. Hence, designers of HMIs are called to instantiate them considering the specific requirements and characteristics of the users and the working tasks of the application at hand.
KW - Human factors
KW - user centered design
KW - user interfaces
UR - http://www.scopus.com/inward/record.url?scp=85099357673&partnerID=8YFLogxK
U2 - 10.1109/TASE.2019.2941541
DO - 10.1109/TASE.2019.2941541
M3 - Article
AN - SCOPUS:85099357673
SN - 1545-5955
VL - 18
SP - 164
EP - 175
JO - IEEE Transactions on Automation Science and Engineering
JF - IEEE Transactions on Automation Science and Engineering
IS - 1
M1 - 8863652
ER -