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Studies on the construction defects and quality deviations have been commissioned and published in many countries, showing the global status of the issues related with construction defects. Therefore, the quality of the adapted practices in construction projects can be improved if the pattern of the sub-task, specifically the quality deviations and construction defects from the requirements and specifications is identified and understood. The purpose of this paper is to improve understanding of the behavior and pattern of the more sensitivity sub-task requirements (STRs) through the anatomy process of a particular task.

Six criteria have been classified for the levels of the estimated STRs quality deviations. The proposed study classifications were examined through the 3,030 cases of 17 STRs from compression concrete members (i.e. column).

Most of the STRs were found to be prone to deviations and the sensitivities of the STRs toward deviations and defects are varied across all STRs. The study reveals that three of the 17 STRs were observed as perfect works, ten STRs as acceptable works and four STRs as defective works.

The study found that the sub-task deviation patterns cannot be generalized and must be individually studied to recommend the appropriate proactive measures.

The aim of this paper is to propose an optimization method for determining the emergency action, in which the compatibility between emergency alternatives and the collaborative relationship between departments are considered.

The individual emergency cost and individual emergency effect of each emergency alternative are calculated. And the collaborative emergency cost and collaborative emergency effect associated with a pair of emergency alternatives are calculated. Then, a bi-objective programming model maximizing the total emergency effect and minimizing the total emergency cost is constructed. A novel nondominated sorting genetic algorithm II (NNSGA II) is designed to solve the constructed model, subsequently. Finally, an example is given to illustrate the use of the proposed method, and the performance of NNSGA II is evaluated through a simulation experiment.

This paper proposes an effective method to manage complex emergency events that requires the coordinations of multiple departments. Also, this paper provides a new algorithm to determine an appropriate emergency action that performs well in managing both the emergency cost and emergency effect.

The findings contribute to the current methods in the field of emergency management. The method is used for dealing with the individual information of emergency alternatives and the collaborative information associated with a pair of alternatives.

IEEE Ontologies for Robotics and Automation Working Group were divided into subgroups that were in charge of studying industrial robotics, service robotics and autonomous robotics. This paper aims to present the work in-progress developed by the autonomous robotics (AuR) subgroup. This group aims to extend the core ontology for robotics and automation to represent more specific concepts and axioms that are commonly used in autonomous robots.

For autonomous robots, various concepts for aerial robots, underwater robots and ground robots are described. Components of an autonomous system are defined, such as robotic platforms, actuators, sensors, control, state estimation, path planning, perception and decision-making.

AuR has identified the core concepts and domains needed to create an ontology for autonomous robots.

AuR targets to create a standard ontology to represent the knowledge and reasoning needed to create autonomous systems that comprise robots that can operate in the air, ground and underwater environments. The concepts in the developed ontology will endow a robot with autonomy, that is, endow robots with the ability to perform desired tasks in unstructured environments without continuous explicit human guidance.

Creating a standard for knowledge representation and reasoning in autonomous robotics will have a significant impact on all R&A domains, such as on the knowledge transmission among agents, including autonomous robots and humans. This tends to facilitate the communication among them and also provide reasoning capabilities involving the knowledge of all elements using the ontology. This will result in improved autonomy of autonomous systems. The autonomy will have considerable impact on how robots interact with humans. As a result, the use of robots will further benefit our society. Many tedious tasks that currently can only be performed by humans will be performed by robots, which will further improve the quality of life. To the best of the authors’knowledge, AuR is the first group that adopts a systematic approach to develop ontologies consisting of specific concepts and axioms that are commonly used in autonomous robots.

This study seeks to extend previous research on experts with mainly ad‐hoc groups from laboratory research to a field setting. Specifically, this study aims to investigate experts' relative importance in team performance. Expertise is differentiated into two categories (task functions and team functions) and the paper aims to investigate whether experts in task and team functions predict team performance over and above the team's average expertise level.

Longitudinal, multi‐source data from 96 professional software design engineers were used by means of hierarchical regression analyses.

The results show that both expert members in task functions (i.e. behavior that aids directly in the completion of work‐related activities) and the experts in team functions (i.e. facilitation of interpersonal interaction necessary to work together as a team) positively predicted team performance 12 months later over and above the team's average expertise level.

Samples from other industry types are needed to examine the generalizability of the study findings to other occupational groups.

For staffing, the findings suggest that experts are particularly important for the prediction of team performance. Organizations should invest effort into finding “star performers” in task and team functions in order to create effective teams.

This paper focuses on the relationship between experts (in task functions and team functions) and team performance. It extends prior research on team composition and complements expertise research: similar to cognitive ability and personality, it is important to take into account member expertise when examining how to manage the people mix within teams. Benefits of expertise are not restricted to laboratory research but are broadened to real‐world team settings.

Facility maintenance is critical for the operation and management of petrochemical plants. Maintenance work completed with higher productivity eventually contributes to better plant performance. Mechanization reduces workforce demand and can increase the productivity of maintenance work. The purpose of this paper is to assess the current mechanization level of the maintenance activities and then identify applicable technology solutions for productivity improvement in petrochemical facility maintenance.

This paper utilizes a mechanization level assessment method for global maintenance data collection and analysis. Subject matter experts’ interviews and market scanning were used to identify corresponding technology solutions.

The study discovered numerous maintenance activities with lower mechanization levels and identified more than 50 technology solutions applicable for maintenance productivity improvement.

This paper provides a roadmap for petrochemical maintenance work participants to assess their mechanization level status quo and identify technology solutions for higher maintenance work productivity. The method adopted is replicable and customizable for further applications with different plant conditions in the petrochemical sector and other industrial contexts.

The purpose of this paper is to develop a model considering synergy effect for prefabricated construction service combination selection.

This research defines prefabricated construction service as a service-led construction method that meets the specific requirements of clients. Based on network theory, the multi-dimensional collaborative relationships of the prefabricated construction inter-services are formulated. The synergy effect is quantitatively calculated through the linear weighting of the strengths of collaborative relationships. Further, a weighted synergy network (WSN) is developed, from which a service composition selection model considering the synergy effect is established. Then, a genetic algorithm is employed to implement the model.

The results showed that (1) when the number of prefabricated construction services is increased, the synergy effect of combination options is enhanced; (2) The finer-grained prefabricated construction services, the stronger the synergy effect of service combination; (3) Clients have heterogeneous preferences for collaborative relationships, and there are differences in the synergy effect of service combination.

The contribution of this research includes proposed a method to quantify the synergy effect from the perspective of collaborative relationships, explored the specific procedure for the prefabricated construction service combination selection under the service-led construction, and provided a reference for promoting the development in construction. Besides, the model proposed could be applied to prefabricated construction service composition selection with diverse research boundaries or client preferences by executing the same procedure.

Multi-manned assembly lines are designed to produce large-sized products, such as automobiles. In this paper, a multi-manned assembly line balancing problem (MALBP) is addressed in which a group of workers simultaneously performs different tasks on a workstation. The key idea in this work is to improve the workstation efficiency and worker efficiency of an automobile plant by minimizing the number of workstations, the number of workers, and the cycle time of the MALBP.

A mixed-integer programming formulation for the problem is proposed. The proposed model is solved with benchmark test problems mentioned in research papers. The automobile case study problem is solved in three steps. In the first step, the authors find the task time of all major tasks. The problem is solved in the second step with the objective of minimizing the cycle time for the sub-tasks and major tasks, respectively. In the third step, the output results obtained from the second step are used to minimize the number of workstations using Lingo 16 solver.

The experimental results of the automobile case study show that there is a large improvement in workstation efficiency and worker efficiency of the plant in terms of reduction in the number of workstations and workers; the number of workstations reduced by 24% with a cycle time of 240 s. The reduced number of workstations led to a reduction in the number of workers (32% reduction) working on that assembly line.

For assembly line practitioners, the results of the study can be beneficial where the manufacturer is required to increased workstation efficiency and worker efficiency and reduce resource requirement and save space for assembling the products.

This paper is the first to apply a multi-manned assembly line balancing approach in real life problem by considering the case study of an automobile plant.

The purpose of this paper is to develop a bi-objective optimization framework to select prefabricated construction service composition. An improved algorithm-genetic simulated annealing algorithm (GSA) is employed to demonstrate the application of the framework.

The weighted aggregate multi-dimensional collaborative relationship is used to quantitatively evaluate the synergistic effect. The quality of service is measured using the same method. The research proposed a service combination selection framework of prefabricated construction that comprehensively considers the quality of service and synergistic effect. The framework is demonstrated by using a GSA that can accept poor solutions with a certain probability. Furthermore, GSA is compared with the genetic algorithm (GA), simulated annealing algorithm (SA) and particle swarm optimization algorithm (PSO) to validate the performance.

The results indicated that GSA has the largest optimal fitness value and synergistic effect compared with other algorithms, and the convergence time and convergence iteration of the improved algorithm are generally at a low level.

The contribution of this study is that the proposed framework enables project managers to clarify the interactions of the prefabricated construction process and provides guidance for project collaborative management. In addition, GSA helps to improve the probability of successful collaboration between potential partners, therefore enhancing client satisfaction.

The purpose of this paper is to share personal experience on the early stages of taxonomy construction, reflecting on the potential role of contextual classification techniques as applied by the records management profession as a tool in effectively organising information, resources and services within intranet and/or portal environments. The paper also aims to assess the additional benefits to be secured where linking content to business purposes can create or reveal new meaning.

The paper draws on experience, personal opinion, published literature and discussions with peers to assess the applicability of contextual classification as a tool to support taxonomy development.

The paper concludes that classification of information, resources and services within intranet and/or portal environments using a citation order of function, activity, task, sub‐task is likely to be of significant value, requiring further investigation to fully assess impact and applicability. Contextual classification receives much discussion in general records management terms, however its applicability in supporting portal and/or intranet development appears to receive little attention. The requirement to generate improvements in information retrieval from a host of on‐line services (of which taxonomy development is one example) is reinvigorating the role of the informational professional. Given the criticality of improving the management and retrieval of information it is desirable that stronger interdisciplinary links are established across the information profession to further develop “information retrieval” as a subject discipline.

The article suggests that the role of contextual classification to organise information, resources and services within intranets/portals requires further investigation and reflection to assess its applicability, value and impact. Initial findings and reflection of the application of contextual classification in the design of elements of a university portal taxonomy have proven to be successful, suggesting that wider discussion and reflection is now required. It is also suggested that the information profession take steps to build stronger interdisciplinary links to advance the development of information retrieval as a subject discipline.

The purpose of this paper is to use de Sitter's design theory to show how organizational structures can be designed so as to attenuate organizational disturbances and amplify regulatory potential. It is argued that organizational structures with low values on so‐called design‐parameters are themselves no source of disturbances and have the required built‐in regulatory potential.

Key concepts from de Sitter's design theory are introduced and used to show how structures can attenuate disturbances and amplify regulatory potential.

The analysis in this paper deepens our understanding of the role of organizational structures for dealing with organizational complexity, and of the design parameters that should be manipulated to achieve structural attenuation and amplification.

Having a structure permitting organizations to attenuate and amplify is a crucial condition for organizational viability. This paper provides guidelines for the design of such structures.

This is one of a limited number of studies that makes apparent how general insights from (management) cybernetic (e.g. viability, attenuation and amplification) may be realized in organizations by their structural design.