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Modularization fails to adequately meet the diverse customer requirements and the product operational data for complex equipment of port shipping (CEPS). To address this challenge, we propose a module configuration design approach (MCDA) that incorporates module parameter planning (MPP) and service module customization (SMC). Initially, the design ranges and weights of functional requirements are established using fuzzy information derived from customer requirements, facilitated by fuzzy quality function deployment. Subsequently, a multi-objective model of MPP is developed, incorporating the cost utility, information content, and delivery time of module and product based on a probabilistic assessment of module instances from operational data. The non-dominated sorting genetic algorithm II (NSGA-II) is employed to derive the solution set for MPP. The personalized configuration of the Pareto solution set for SMC is derived based on each objective function pair. Finally, we illustrate the effectiveness of the proposed approach through a case study involving a wheel loader and method comparison.

This paper presents the definition of a Reference Application Architecture for the Customer Relationship Management (CRM) domain. The definition of the Reference Application Architecture is done by extracting best practices from five CRM commercial solutions: SugarCRM, Microsoft Dynamics CRM, Sage CRM, Oracle Siebel CRM and Salesforce CRM. The CRM Reference Architecture was developed considering the shared functionalities and information entities among these commercial solutions. In the Reference Architecture the authors identify six modules in the CRM system and five systems, which interact with the CRM system. The six CRM modules are: Account module, Sales module, Marketing module, Service module, Scheduler Module and Administration module. The five interacting systems are: Portal, Contact Center, Document and Knowledge Base Management system, Workflow system and Reporting and Analytics system. Then the authors apply the defined architecture in a case study from the Portuguese Public Administration, the Citizen Spaces provided by the Agency for the Administrative Modernization. The authors compare the current state of the Citizen Spaces with a possible architecture reached through the Reference Architecture, and assess the benefits and pitfalls of the purposed architecture.

Proposing an approach of service resource configuration optimization driven by customer requirements to address the issue of service resource configuration optimization in the context of personalized customization. Firstly, the importance judgment matrix, KANO model, and competitiveness evaluation are integrated to evaluate the relative importance of customer requirements. Secondly, the House of Quality (HoQ) and the intermediary variable “technical attributes” are utilized to determine the weight of each service module and its correlation with customer requirements. Afterwards, due to the varying customer requirements, the service candidate itemsets under the same service module will differ. To address this, a “one-to-many” relationship mechanism is introduced between the service module and service candidate itemsets. The service candidate itemsets are determined based on the correlated customer requirements. On this basis, the customer’s perceived utility is determined by applying the four types of utility measure functions. The service resource configuration scheme is established by formulating and solving an optimization model. Finally, the viability and efficacy of the approach are demonstrated with an example of living room customization by a customization company, utilizing an improved genetic algorithm (IGA).

PurposeService modularity promotes efficiency at the provider end of the supply chain and customisation at the customer end. The purpose of this paper is to investigate how logistics service modularity contributes to sustainable development through the means of energy efficiency. This is analysed in the context of logistics services for household waste collection.Design/methodology/approachA single case study methodology with embedded units is adopted where semi-structured interviews were conducted with a waste service provider (WSP) and buyers (municipalities) in Sweden, focussing on five types of logistics services for waste collection: collection of food and residual waste at apartments and one-family houses, as well as collection of gardening waste. Service modules are identified and analysed by blueprinting the service.FindingsThe findings show different service modules – standardised or customised – and their contribution to sustainable development operationalised through energy efficiency. Principles for an energy-centric service design are proposed.Research limitations/implicationsThe research is limited to Swedish household waste collection setting. Promising efficiency through standardisation, logistics service modularity has a potential to improve energy efficiency as well. This neglected link between sustainability and service modularity offers fruitful research avenues.Practical implicationsThis research is of practical relevance to waste logistics service providers and the municipality by suggesting principles for energy-centric service design. The service blueprint enables using logistics service modularity for improving energy efficiency in different logistics service settings.Originality/valueThis research incorporates an environmentally sustainable development perspective into logistics service modularity and contributes to the literature by exploring how energy efficiency is improved by modular design of logistics services. Furthermore, the study is one of the first to use service blueprinting to analyse logistics service modularity, providing a methodological contribution to that field in general and logistics in particular.

Companies are seeking more and more to offer customized goods and services to customers to be able to satisfy their needs. Several methods emerged to fulfill the needs of customization without affecting the performance of the company. Modularity has been considered as an effective method to address the challenges regarding variety management in the product and service domain. It has been addressed in the product domain but rarely in the service domain. This paper aims to provide a method to modularize a service-oriented system that consists of products and services. The method uses a set of modularization criteria and clustering techniques to form service-oriented system modules (product and/or service modules). The output of the clustering process is evaluated using indicators to provide decision-makers with insights into potentially preferred clustering alternatives. A test case is presented in order to show the applicability of the method.

In order to solve the problems of large demand for power business and small number of customer service, an intelligent customer service questioning and answering a system for power business scenario based on AI technology is designed. The approach first uses the particle swarm optimization algorithm to automatically classify the question attributes and then uses the fuzzy c-means clustering algorithm to match the answers with the highest similarity to the questions and return to the customers. The system collects the questions raised by customers through the acquisition module, uploads the question work order to the knowledge base through the information assistance module, and stores the preprocessed questions to the knowledge base. After completing the problem attribute classification through the particle swarm clustering algorithm classification model in the batch analysis and calculation module, the question answers are matched through fuzzy c-means clustering. At the same time, the similarity of different keywords is calculated to find a series of related questions. After the obtained data are analyzed in real time through the self-service customer service module, the answer is extracted and fed back to the customer, and the question answer is presented to the customer in the system interface. The experimental results show that the designed system has low worst-case time complexity, which is up to 0.35 only. The reason is that the system in this paper can use priority information to deal with the problems raised by customers, which is different from the past work where dealing with customers request via priority information is not used. The system can give the corresponding answers according to the customer’s options. It has convenient operation, high integrated control ability, and good information management performance. Compared with the traditional approach which could waste a lot of resource and data, the proposed approach can reduce the differences between problem data, eliminate invalid data, and simplify the data classification process. The application of the system can effectively accelerate the information transmission efficiency of the power company and can be used for power exchange platform automation in the future.

With the development of the information age, business systems are becoming more and more complex. System development and maintenance are facing huge challenges. In response to this problem, aunified application development platform based on the microservice architecture is proposed.Compared with the traditional single-architecture architecture, the microservices architecture can split a large and complex application system into a series of service modules that can be independently developed, tested, deployed, operated, and upgraded. This enables the application expansion and application reduction for a large number of Internet companies. Developing complexity and implementing agile development provide more effective methods. This article through a detailed case analysis - the development of the cloud platform system, describes the specific application of the microservice architecture in the actual project development, and discusses the advantages of the traditional single architecture model for the service architecture to build the system. Through research and analysis, it is concluded that the microservice architecture has certain guiding significance for solving problems that may be encountered in enterprise-level applications.

This article presents the data acquisition, exploratory data analysis, model training, evaluation, and use of hyperparameters in a machine learning model that will be used to predict telemetry data from the Amazonia-1 satellite. The Amazonia-1 satellite was launched in 2021, it uses the Multi-Mission Platform as a service module and has a Wide Field Imager imaging camera. Its power subsystem has 715 telemetries with distinct data types that will be used as dependent and independent variables. The amount of telemetry data generated daily is large, making manual analysis of this data unfeasible. The ensemble XGBoost machine learning algorithm is used to predict the values of the dependent variable D008 “Battery Module 1 Voltage” that belongs to the electric power subsystem. For the evaluation and performance Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and R2 are used. The final learning model resulted in the coefficient of determination (R 2 ) with 99.99%, MAE of 0.005749, and RMSE of 0.007727. After the cross-validation step, RMSE reached 0.006888. The execution time was 57 minutes and 32 seconds. Based on these numbers, we can consider that the machine learning model built reached a good result, especially when used with cross-validation.

PurposeThis paper explores the enablers of modular healthcare services.Design/methodology/approachA survey-based approach was adopted with specialised hospitals as the unit of analysis. A structural model was developed based on a literature review and assessed using a cross-sectional research design. A 23-indicator questionnaire was circulated among service providers in the healthcare system across India, and 286 valid responses were received. The data were analysed using partial least squares-structural equation modeling (PLS-SEM).FindingsThe results reveal that professional competence, technological versatility, clear division of tasks, channelised flow of information and professional autonomy act as enablers that may drive modular service delivery.Research limitations/implicationsBy examining service providers' perspectives, this paper highlights the influence of the identified enablers on modular service delivery in healthcare organisations.Practical implicationsFor practitioners, the study provides suggestions for designing patient-centric healthcare services via modular healthcare delivery. The identified structural relationships can facilitate immediate corrective actions and the formulation of future policies. The findings will help practitioners foresee opportunities for patient participation in value co-creation, meet patients' varying needs, decompose service offerings, mix and match components develop sets of rules as interfaces between service modules and design service packages on an ongoing basis.Social implicationsThis study underscores the emergence of patient-centric care and may aid the design of processes that deliver health to the patient as a person.Originality/valueThis paper identifies and empirically validates relationships between healthcare service delivery processes and modular service delivery.

A novel high frequency digital transceiver scheme using audio port as signal modulation and demodulation interface is proposed. The system adding human-computer interaction module, business service module, base station modulation and demodulation module, shipboard modulation and demodulation module, and using advanced modern digital signal processing algorithm to complete signal modulation and demodulation in digital domain, which overcomes the anti-interference ability of analog demodulation circuit poor power, low spectrum utilization, poor user experience and other shortcomings. The simulation results show that when SNR of the baseband is 4.9dB, the BER of the system can reach about 10 −4 , the design scheme can meet the ITU-R M.2058-0 recommendation and the actual communication requirements.