9. Developing Maintenance Applications

The system of preventive maintenance for various types of equipment is considered. To identify the need for managerial influence on the processes of maintenance and repair of the product, the coefficient of variation of the maintenance (repair) cycle is proposed. This coefficient is formed by the values of operating time or work between stops for maintenance or repair. To determine its numerical value, it is recommended to use such concepts as "maintenance (repair) cycle" and "frequency of maintenance (repair)". The values of the coefficient characterizing the stability of the process of repair and maintenance of the product are determined. These values of the coefficient are proposed to be used to justify the need to analyze the causes of failures or, in other words, the instability of the repair and maintenance process. The main managerial influences on the process of maintenance and repair are determined, which can be taken as a result of the analysis of the causes of failures. These include: the decision to search for a technical service provider, expanding the competencies of employees, updating the material base. Modern industry 4.0 tools allow you to get the required level of quality when working with a large data stream. The use of neural network technology in various technical service management tasks is due to some advantages over classical methods of statistical processing of results. The experiments of various authors are presented in which it is shown that neural network technologies are able to interpret graphic information, justify its use in technical diagnostics at the stage of analyzing diagnostic information in the form of oscillograms, which allows the use of complex diagnostic equipment in the absence of experts. A neural network simulation was carried out to recognize defects in bearing assemblies. As a result, the created neural network recognized the type of defect in accordance with the matrices of input signals and the output matrix of types of defects, which makes it possible to develop a mechanism for improving technical service using neural networks as a tool for analyzing diagnostic information in the absence of experts in this field.

At present, in China’s automobile manufacturing industry, the main problem is the manufacturing of parts and on-board equipment. Most domestic industries still adopt the step-by-step production of parts, and each manufacturer customizes the required parts according to the scale and production needs of its own enterprise. This situation is easy to cause unstable quality of parts and serious unqualified quality inspection problems. Based on the above situation, we study the high-quality development, parts quality optimization, and remanufacturing of auto parts manufacturing industry with the support of machine learning model. Firstly, based on the analysis of auto parts procurement and production mode, this paper briefly describes the basic problems in the manufacturing process of auto parts in China. Machine learning technology is used to count the changes of quality data in manufacturing, and the quality standard is reflected in the learning model. The machine learning algorithm is used to diagnose and analyze the faults of auto parts and equipment, so as to turn high-quality production to high-quality production. The projection feature extraction algorithm is used to quantitatively analyze the low quality state of automobile parts. Finally, 3D printing technology is used to solve the quality manufacturing problem of parts with high-precision requirements, and the later materials are processed again to achieve the purpose of remanufacturing planning. The results show that the transformation of auto parts manufacturing to high quality can improve the economic development of the auto industry and meet the needs of modern society. The data analysis of parts controlled by machine learning model can help the precision manufacturing of automobile parts.

The current problem of the MRO organizations is competitiveness in the environment of aircraft maintenance, in which the main task is to improve the quality of the maintenance and reduce aircraft downtime. This study examines how the MRO can improve the procedures of individual aircraft maintenance by implementing Lean tools, in the combination of Six Sigma methods. The aim is analyzing the maintenance processes to determine the existing problems to minimize downtime of the aircraft in this area. Using the data collected from the experts of the MRO, airlines, and an equipment manufacturer, an analysis was made on engine replacement processes. Consequently, , a novel tool is proposed utilizing hydraulic lift engine hoists. The result shows that this approach allows to eliminate unnecessary tasks from the Aircraft Maintenance Manual (AMM) and also reduces the turnaround time by more than 7 h in a single process. The measurement which is based on the final results validates the main contributions for MRO organizations through savings in time and human resources, thereby reducing maintenance cost and aircraft downtime and satisfying the customer.KeywordsMROMaintenanceLean Six SigmaEngineLean implementation

Formal Rules in Product Development: Sensemaking of Structured Approaches

Many scholars consider the use of formal structured approaches to manage product development as very significant for successful product innovation. Others consider them a predictor of the likely outcome of the processes. Structured approaches can be considered management technologies for product development. Prior research has addressed the design of structured approaches and has measured how different types or generations of these are related to different processes and outcomes in different ways. However, only limited research has addressed how managers and employees actually understand and makes sense of these methods. This paper investigates how structured approaches are translated through a number of interpretations into daily practices. The research draws on research in sociology and management accounting to analyze structured approaches for product development as a managerial technology that consists of rules that individuals must understand (i.e., make sense of). The paper presents arguments for building a model of factors that influence the sensemaking of structured approaches for product development based on Scandinavian cases. First, structured approaches are presented as a type of managerial technology that consists of rules. Second, a framework to classify structured approaches for product development according to their degree of elaborateness and exhaustiveness is derived. This helps to identify the types of rule systems in companies—and how these influence everyday practices. The sensemaking from rules to practice is implemented through a number of translations, based on the context, the history, and the authorized statements and feedback processes. Empirical findings show that structured approaches differ both with respect to their degree of elaborateness and exhaustiveness. Additionally, firms differ greatly in terms of how rigorously they enforce the rules. Furthermore, the importance assigned to them by functional managers and project managers differ greatly. Even companies with extensive and elaborate rule regimes enforce the rules in a flexible manner, and rules are often applied at the discretion of project managers. Practices are influenced by the interpretation, use, and feedback from senior managers. Observations make it possible to develop a model for the sensemaking processes that influences how a specific structured approach through sensemaking is altered, modified, and sometimes even cut off from influencing innovation processes. The sensemaking of rules might reverse elaborate and exhaustive rules into quite flexible systems in practice. One implication of this is that individual sensemaking of structured approaches for product development thus needs to be analyzed to understand managerial practices. Another implication is that it cannot be assumed, a priori that formal approaches are the same as exercised practices.

Software reuse has drawn much attention in computing research. Domain analysis is considered a prerequisite to effective reuse of existing software. Several approaches and methodologies have been proposed for domain analysis or domain modeling, but not many case studies have been reported in the literature. The first objective of this paper is to present the concept and practical experiences of a domain analysis approach in discrete-event simulation in manufacturing — generic /specific modeling. A second objective of this paper is to present a meta-model based on the generic/ specific approach from the software engineering perspective. The steps and knowledge required to build the model are described. Domain analysis lessons learned from the generic/specific approach in discrete-event simulation are discussed. Classification of this domain modeling approach was conducted through the Wartik and Prieto-Diaz criteria. The classification will facilitate the comparison with other domain analysis approaches. Similar modeling concepts or techniques may be beneficial to other researchers in their own application domains.

<div class="section abstract"><div class="htmlview paragraph">Enhancing the comfort for passengers, airlines are constantly increasing the number of services within the aircraft cabin such as meal ordering directly from passenger seats. The payment and menu selection can be completely processed by means of a passenger-individual airline user account also considering the remaining inventory of the galley. The implementation of such type of services is supported by digitalization of cabin business processes. For these new services the airline requires a high availability of the process-related system functions to ensure airline’s revenue and customer satisfaction.</div><div class="htmlview paragraph">A possible approach to reach the target of high availability of these functions is to use the trend of digitalization for improving function-relevant maintenance processes within the aircraft cabin. This requires an introduction of flexible communication architectures to enhance the existing maintenance process by establishing an automated fault detection, root cause analysis, and/or even fault prediction. For implementation it is necessary to provide system data and parameters digitally, e.g. by sensor measurements or an online evaluation of already existing system data logs. An example is the working light within the aircraft galley used to create an appropriate working environment for the cabin crew to prepare ordered meals for the passengers. Currently, fault detection is only possible by identifying its failure effect, i.e. a not illuminating lighting unit. However, by measuring the current consumption of the light source via a digital sensor, it would be possible to detect a changing trend in the current consumption and, in turn, triggering a maintenance task to replace the light before it actually fails. The evaluation of such current measurement with the resulting fault prediction would expand the maintenance system by a new function.</div><div class="htmlview paragraph">This paper describes how digitally supportable maintenance processes for any cabin system can be systematically identified and which system modifications are necessary for realization. Further-more, a methodology for cost and benefit assessment is introduced to find the right level of digitization for the cabin system under analysis.</div></div>

A mass mortality of the most abundant zooplanktophagous fish due to an infectious gill disease eliminated almost the entire population of this species in the Eastern basin of the Lake Annone, Italy in'75-76, while no mortality occurred in the Western basin. This event offered the opportunity to study whether a recently developed structural dynamic modelling approach would be able to describe the changes in the properties of zooplankton observed in the Eastern basin as a result of an abnormal high fish mortality in August '75. As a change in size of zooplankton was observed (from 1000 µm to1600 µm) it would even be possible to see if the modeling approach could describe the actually observed changes in structure(properties of the organisms, in this case zooplankton). The modelling approach uses the thermodynamic concept exergy as a goal function which determines the current changes of the properties of the species included in the model description. From the study it can be concluded that this modelling approach was able to describe the focal state variables of the model (phytoplankton, zooplankton and fish) in accordance with the observations from '75 to '76 and also to assess the actually observed changes in zooplankton size.

Formal requirements modeling and traceability management are essential for effectively implementing Model-Based Systems Engineering (MBSE). However, few studies have explored the integration of requirement modeling, traceability management, and verification within MBSE-based systems engineering methodologies. Moreover, the predominant modeling language for MBSE, SysML, lacks sufficient capabilities for requirement description and traceability management and for depicting physical attributes and executable capabilities, making it challenging to verify functional and non-functional requirements collaboratively. This paper proposes an integrated approach for requirement modeling, traceability management, and verification, building on the previously proposed integrated modeling and the simulation language called X language. Our contributions primarily include defining the ReqXL specification for MBSE-oriented requirement modeling based on X language, proposing an algorithm for automatically generating requirement traces, and an integrated framework for requirements modeling, traceability management, and verification was developed by combining the X language with ReqXL. These functionalities were customized on the self-developed integrated modeling and simulation platform, XLab, which is specifically tailored for the X language. Furthermore, we showcase the efficacy and promise of our approach through a case study involving the design of an aircraft electrical system.

This paper investigates the prediction capability of deterministic methodologies in estimating construction productivity for earthmoving operations. Published literature includes several estimation methodologies stemming from (a) equipment manufacturers’ manuals, (b) editions from German contractors’ associations or individual researchers and (c) textbook editions. The purpose of this research is to assess the yielded productivity estimation results under the prism of 14 estimation methodologies. It is – to the authors’ best knowledge – the first research attempt for the comparative evaluation of such a diverse set of estimation methodologies, with the aim of quantifying their effects on the operations analysis in earthmoving works. A uniform mathematical modelling approach is used to formulate the relevant estimation equations and, subsequently, a real-case scenario of an earthmoving project in Greece is used as a benchmark against which the robustness of each methodology is assessed. A sensitivity analysis on main productivity factors concludes the research. The preliminary results indicate that equipment manufacturers’ methods are more optimistic and present higher sensitivity to specific productivity factors (e.g. swing angle, excavation depth), whereas the German-oriented approaches are more conservative with less variability due to differing productivity factors.

The structure of corporate computer networks and the classification of problems by its levels were considered. The main group of elements (application software, system services, and data banks), the corporate information system, is selected as the object of this research. The maintenance stage of corporate information systems is highlighted in the context of labor costs at this stage of the life cycle. For clarity, the process of maintenance is represented by a closed iteration system, where the duration and list of tasks depend on the problem type. In accordance with ISO 14764-2003, the three-level classification is proposed for the types of problems and activities in the maintenance stage of the corporate information system. The statistical analysis was performed of the time costs of maintenance using the proposed classification in the context of tasks and types of errors. Based on the results of the analysis, the main reasons for the complexity of the maintenance of corporate information systems were identified. These reasons determined the main direction of further research - processing of data banks in real time mode for localization of the client’s business process. This will reduce the time and financial costs of maintenance.

Risk is an important factor affecting the success of complex equipment research and manufacturing, so how to deal with the risk properly has become the key to risk management of complex equipment cooperative research and manufacturing. In view of this, considering that the choice of risk response schemes for complex equipment research and manufacturing is a consensus issue of group negotiation, this paper exploits group decision‐making and utility theory to establish a risk disposal scheme selection model for complex equipment development based on group negotiation consensus, and then a case verifies the validity and rationality of the proposed model. The results show that the consensus scheme selection problem proposed in the paper effectively combines the preference value and utility, considers the supplier’s risk preference behavior, and achieves the multisubject consensus scheme.

Integrated consideration of production planning and maintenance processes is a real world assumption. Specifically, by improving the monitoring equipment such as various sensors or product-embedded information devices in recent years, joint assessment of these processes is inevitable for enhancing the level of the system optimization. By means of this equipment, managers can benefit from a condition-based maintenance (CBM) for monitoring and managing their system. The chief aim of the paper is to develop a stochastic maintenance problem based on CBM activities engaged with a complex applied production problem called flexible job shop scheduling problem (FJSP). This integrated problem considers two maintenance scenarios in terms of corrective maintenance (CM) and preventive maintenance (PM). The activation of scenario is done by monitoring the degradation condition of the system and comparing the associated value by predetermined PM and CM levels. Moreover, to make it more realistic, the developed problem allows breakdown of the system between inspection intervals. The event time and duration of performing the maintenance activities are also considered stochastic. The developed methodology copes with high stochastic complexity of proposed problem through simulation-based optimization (SBO) approach, which works based on harmony search optimization algorithm. The developed items of SBO are discussed on different generated test problems and assessed through statistical methods and new visualization approach. Numerical example shows that the proposed method is practical for proposed integrated CBM and FJSP problem. It also offers a basis for any implementation of CBM on production problems.

Authors: Abolfazl Akhondzadeh, ORCID: https://orcid.org/0000-0001-8160-3425 Master of Science, PhD Candidate, Researcher, Yazd University of Science and Art, Iran Pages: 86-96 DOI: http://doi.org/10.21272/sec.3(4).86-96.2019 Download: Views: Downloads: 43 6 Abstract The final goal of this study is to provide a model with structural modeling approach of virtual R & D implementation in Iranian ceramic tile companies and small and medium-sized industries and services are one of the broadest fields of activity of manufacturing and economic enterprises that are of great importance. Accordingly, the establishment and expansion of research and development systems in order to infuse new sciences and technologies into this industry is of great importance. Over the past few decades, in a highly competitive market, the development of new products has long been considered as a major contributing factor to the survival and growth of SMEs and manufacturing units and economic enterprises have a great desire to create and develop R & D and investment systems for their efficiency so the necessity of conducting this research was created for Iranian companies because SMEs are considered as engines of economic growth, particularly in developing countries and in a day-to-day market for freedom, the survival and continuity of SMEs depend on their ability to enhance their performance and production that are in accordance with international standards. The questionnaires and interviews used to examine the research questions. It was distributed among 114 experts after ensuring the reliability and validity. The research strategy is a survey-correlation questionnaire that has been compiled by a researcher-made questionnaire. The results of this study showed that the technology structure in virtual teams does not directly affect the implementation of virtual R & D. The knowledge structure of the individuals and the process structure can have a direct effect on the implementation of virtual R & D in the other hand this paper acknowledges the progress made over the past several decades, it focuses on the challenges and limits of Iranian Tile and Ceramic Companies. Keywords: virtual research and development, small and medium-sized industries, interpretive structural modeling, virtual teams.

Leader’s non-cognitive abilities and knowledge sharing behavior among team members remains a central concern of healthcare teams for the effective team outcomes. As in complex healthcare environment leaders have to confront with contradictory behaviors. Therefore, the research study attempts to address question how exchange of knowledge amongst health professionals who are associated and working in teams enhances the team effectiveness under emotionally competent leadership. Considering the factor; that leader emotional intelligence is a critical proficiency which may influences sharing of knowledge in health care teams, in terms of final outcomes and effectiveness criteria. A cross-sectional study with structural modeling approach by using Smart PLS was employed to examine the mediating effect of knowledge sharing on relationship of leader emotional intelligence and team effectiveness Data were analyzed by means of a self-reported questionnaire from 225 health care professionals who were working with teams. The study findings indicated knowledge sharing within interprofessional health care teams is influenced by leader emotional intelligence. Furthermore, it was shown that leader emotional intelligence and knowledge sharing is positively related to team effectiveness. Mediation analysis revealed that knowledge sharing mediates the relationship between leader emotional intelligence and team effectiveness. In practice, the results of the study provide a valuable starting point for healthcare leadership to educate them on emotional competencies and encourage knowledge sharing as it deemed important for achieving effectiveness.