Effective Production Management Research Articles

Evaluation of the State of Innovative Activity of Machine-Building Enterprise

Abstract The innovative activity of machine-building enterprises is the main guarantee of their sustainable and effective development, which makes it possible to compare technical and technological innovation in the production of products in different periods and between different enterprises in points. Quantitative numerical assessment of the innovative component of the enterprise is a prerequisite for developing a strategy for further effective production management. After all, in addition to financial performance indicators, technical innovations play a decisive role in the modern market environment, although little attention is paid to them. In the work, based on organizational and technical modeling and logical methods of exploratory evaluation, the author’s method of establishing a quantitative comparative level of innovative activity of a machine-building enterprise was built. The developed methodology for evaluating the innovative component of machine-building production is based on three basic criteria: mastering new machines, mastering technological processes, and the effectiveness of implementing design and technological solutions. The first two criteria take into account the nomenclature, novelty, the risk of introducing a new solution and the technical level of products. To determine these criteria, several levels of novelty of machines and technologies are proposed and the author’s understanding of their content is given. The third criterion, the effectiveness of implementation, is evaluated by indicators that take into account the intensity of adjustments at various stages of design. The result of the study is a method of comparative assessment of the level of innovative components of the development of machine-building production with a set of indicators that provide professionals with a tool for monitoring the processes of introducing new equipment and technologies into production and the subsequent formation of an effective innovative strategy for the development of a machine-building enterprise. The capability of the proposed methodology is presented in the given example of evaluating the innovative development (state) of an abstract machine-building enterprise.

Method of Analyzing Technological Data in Metric Space in the Context of Industry 4.0

The purpose of this article was to develop a method of analyzing the manufacturing process with variables indicating product competitiveness and technological capabilities in metric space as a cognitive source. The presented method will facilitate the identification of key development factors within the manufacturing processes that have the greatest impact on the adaptation of the manufacturing enterprise to Industry 4.0. The presented method of manufacturing process analysis integrates a number of tools (SMART method, brainstorming, BOST analysis, 3 × 3 metrics) that enable the implementation of statistical analysis. The model developed makes it possible to apply known mathematical methods in areas new to them (adaptation in the manufacturing area), which makes it possible to use scientific information in a new way. The versatility of the method allows it to be used in manufacturing companies to identify critical factors in manufacturing processes. A test of the developed method was carried out in one of the foundry enterprises, which allowed us to build a series of importance factors affecting effective production management. The methodology is addressed to the management of manufacturing enterprises as a method to assist in analyzing data and building (on the basis of improved manufacturing processes) a competitive strategy.

The Role of Emotional Intelligence in Effective Product management within Digital Environments

The Role of Emotional Intelligence in Effective Product management within Digital Environments

A Method for Estimating Alfalfa (Medicago sativa L.) Forage Yield Based on Remote Sensing Data

Alfalfa (Medicago sativa L.) is a widely planted perennial legume forage plant with excellent quality and high yield. In production, it is very important to determine alfalfa growth dynamics and forage yield in a timely and accurate manner. This study focused on inverse algorithms for predicting alfalfa forage yield in large-scale alfalfa production. We carried out forage yield and aboveground biomass (AGB) field surveys at different times in 2022. The correlations among the reflectance of different satellite remote sensing bands, vegetation indices, and alfalfa forage yield/AGB were analyzed, additionally the suitable bands and vegetation indices for alfalfa forage yield inversion algorithms were screened, and the performance of the statistical models and machine learning (ML) algorithms for alfalfa forage yield inversion were comparatively analyzed. The results showed that (1) regarding different harvest times, the alfalfa forage yield inversion model for first-harvest alfalfa had relatively large differences in growth, and the simulation accuracy of the alfalfa forage yield inversion model was higher than that for the other harvest times, with the growth of the second- and third-harvest alfalfa being more homogeneous and the simulation accuracy of the forage yield inversion model being relatively low. (2) In the alfalfa forage yield inversion model based on a single parameter, the moisture-related vegetation indices, such as the global vegetation moisture index (GVMI), normalized difference water index (NDWI) and normalized difference infrared index (NDII), had higher coefficients of correlation with alfalfa forage yield/AGB, and the coefficients of correlation R2 values for the first-harvest alfalfa were greater than 0.50, with the NDWI correlation being the best with an R2 value of 0.60. (3) For the alfalfa forage yield inversion model constructed with vegetation indices and band reflectance as multiparameter variables, the random forest (RF) and support vector machine (SVM) simulation accuracy was higher than that of the alfalfa forage yield inversion model based on a single parameter; the first-harvest alfalfa R2 values based on the multiparameter RF and SVM models were both 0.65, the root mean square errors (RMSEs) were 329.74 g/m2 and 332.32 g/m2, and the biases were −0.47 g/m2 and −2.24 g/m2, respectively. The vegetation indices related to plant water content can be considered using a single parameter inversion model for alfalfa forage yield, the vegetation indices and band reflectance can be considered using a multiparameter inversion model for alfalfa forage yield, and ML algorithms are also an optimal choice. The findings in this study can provide technical support for the effective and strategic production management of large-scale alfalfa.

Counselling Farmers on Improving the Yield of Flowering Crops through Integrated Apicultural Farming for Wealth Creation

This study focused on counselling farmers on improving the yield of flowering crops through integrated apicultural farming for wealth creation. The researchers used a descriptive survey research design and a sample of 50 participants, including traditional bee farmers, staff of agricultural education, and intending apiarists which were purposively selected from a public state owned university, Bamidele Olumilua University of Education, Science and Technology (BOUESTI). Data was collected using a well-structured questionnaire, which was validated by agricultural science and counselling education experts. The instrument's reliability was established through a pilot test, and the data analysis involved descriptive statistics such as frequency, percentage, and mean scores. The two major focus of the questionnaire was to identify various challenges that hinder subsistence farming of apiculture as wealth creation strategies and to also establish the fear level of those who are interested in bee keeping but are afraid of sting. The challenges identified from the findings of this study included poor credit services, shortage of forage, inadequate training and manpower, poor apiculture policies, diseases affecting honey bees and poor utilization of technology. In addition, the study found that subsistence farmers and intending apiarist exhibited high levels of apiphobia, which negatively impacted their engagement in apiculture. The researchers through group counselling educated participant on strategies for improving apiculture farming, such as effective crop production management, planting of flowering crops like beans, maize, and mango, and selecting suitable apiary locations away from windy areas. To unlearn anxiety and phobia of bee sting, systematic desensitization (a Counselling Therapy) was used to assist both subsistence farmers and intending apiarists. Keywords: Apicultural Farming, Wealth Creation, Apiphobia, Systematic Desensitization. Journal Reference Format: Makinde, V.I. & Ogunjobi, P.O. (2023): Counselling Farmers on Improving the Yield of Flowering Crops through Integrated Apicultural Farming for Wealth Creation. Humanities, Management, Arts, Education & the Social Sciences Journal. Vol. 11. No. 2, Pp 19-32. www.isteams.net/humanitiesjournal. dx.doi.org/10.22624/AIMS/HUMANITIES/V11N2P3

Improving blood product management in placenta accreta patients with severe bleeding: institutional experience

BackgroundPlacenta accrete spectrum (PAS) is a significant risk factor for postpartum hemorrhage and effective blood product management is critical in ensuring patient safety. In PAS patients undergoing cesarean section (CS) blood transfusion management guided by the combined clinical experience of the anesthesiologist and surgeon with point-of-care coagulation testing appears safe and effective. We describe and evaluate our experience and identify potential areas for improvement with blood product management in this patient population. MethodsA retrospective chart review of peri-operative demographic, anesthetic, and obstetric data was conducted for all patients with PAS undergoing CS between 2012 and 2018 at our center. To facilitate a practical evaluation of blood product management, we divided patients into two groups based on the severity of bleeding. ResultsA total of 221 parturients with PAS underwent CS, with 133 in group 1 requiring excessive amounts of transfusion and 88 in group 2 requiring management similar to other uncomplicated CS cases. There were no deaths or instances of disseminated intravascular coagulation, and intensive care unit admission occurred in five cases (2.2%). Patients in group 1 had higher mean nadir values of intra-operative hemoglobin and platelet count. We observed a high rate of missing data for peri-operative measurement of lactate and fibrinogen, PAS grade documentation, and temperature monitoring. ConclusionGiven no significant morbidity or mortality, clinical judgment in experienced centers appears safe for the management of PAS patients undergoing CS. The adoption of an institutional protocol and point-of-care coagulation testing could decrease over-transfusion and associated complications.

Coaxial multi-criteria optimization of a methane steam reforming reactor for effective hydrogen production and thermal management

The advancement in environmental awareness is the recent driving factor of the energy industry development. The market sentiments dictate the commercialization of unconventional energy sources. Thus, generation via hydrogen conversion gains popularity. The presented research regards the enhancement of the steam reforming reaction, used for the production of hydrogen via the conversion of hydrocarbons. The reforming process characterizes by a strong endothermic nature. The rapid course of the reaction leads to the creation of temperature gradients of a considerable magnitude. The presented research strives to alleviate the negative consequences of the reaction character. An original strategy by the name of macro-patterning is suggested as a remedy. The presented research proposes an updated concept, predicting the introduction of coaxial segments to the catalytic insert. The segments may consist of catalytic material or metallic foam applied for local suppression of the reaction. The morphology of specific segments may be altered independently, to allow for additional control of the reforming reaction. The objective of the research is to define the optimal segment composition. The optimization process is based on an in-house procedure implementing a genetic algorithm. The acquired results appear to validate the macro-pattering concept. A significant unification of the temperature field is obtained, with a simultaneous increase in hydrogen productivity.

Função discriminatória de lógica Fuzzy para avaliação de cabras expostas a ocorrência de verminose quanto à resistência, resiliência ou sensibilidade ao parasitismo

Abstract Worm infections pose a significant challenge to goat farming in the tropics. While individual variations in the animals' response to this disease are observed, understanding its genetic component is crucial for establishing effective herd production management, prioritizing the selection of goats with higher resistance to parasitism. This study aimed to assess goat response to worm infection under natural field conditions using data on eggs per gram of feces (EPG), body condition score (BCS), and conjunctival mucosa coloration (FAMACHA©). Cluster analysis and artificial intelligence (AI) techniques were applied to 3,839 data points from 200 individuals in an experimental goat herd in Piauí, Brazil. The study considered the phenotypic expression of resistance, sensitivity, and resilience to worm infection as responses to parasitism. Three clustering methods, namely Ward, Average, and k-means, were employed and compared with fuzzy logic obtained through the CAPRIOVI web software. The analysis revealed statistically significant differences (P<0.05) between the groups of animals classified as resistant, resilient, and sensitive to parasitism. Pregnancy and peripartum were identified as stages of heightened sensitivity to parasitism (P<0.05). Among the clustering techniques, traditional statistical methods exhibited excellent performance, with an overall accuracy percentage exceeding 90.00%. In contrast, CAPRIOVI's fuzzy logic demonstrated lower overall accuracy (77.00%). The clustering methods showed similar efficiency, but differed in terms of the distribution of animals per group, with a tendency towards greater numbers in the resistant category. Fuzzy logic circumvented this limitation by enabling the formation of groups tailored to meet the producer's interests, adding consistency in terms of the animals' response to worm infection. This finding highlights the potential of the software for goat health management.

PENGARUH PENERAPAN METODE MATERIAL REQUIREMENT PLANNING (MRP) DAN METODE ECONOMIC ORDER QUANTITY (EOQ) TERHADAP EFISIENSI BIAYA BAHAN BAKU

<p class="TableParagraph"><em>The production process is an activity that is very important for the survival of the company. Every company, whether a manufacturing company or a service company, must have the same goal, which is to earn a profit, so as to obtain cost efficiency for the supply of plastic raw materials, where the inventory planning is formed, it expects to produce an efficient procurement of raw material costs, meeting consumer demand without going out of stock to the customer. raw materials, by applying appropriate methods in its production. One of them is through effective production and inventory management, namely through the Economic Order Quantity (EOQ) method and the Requirement Planning (MRP) method. The research method used is descriptive quantitative method, quantitative research is a research method based on the philosophy of positivism, used to examine certain populations or samples, data collection using research instruments, data analysis is quantitative/statistical. Descriptive analysis is an activity of inferring raw data in large quantities so that the results can be interpreted. Data collection techniques through interviews and documentation. The results show that the application of the Material Requirement Planning (MRP) method is more influential than the EOQ (Economic Order Quantity) method on the efficiency of raw material costs at PT Polytech Indo Hausen Tanggerang by determining the most economical totality of raw material costs without reducing the quantity in the production process.</em></p>

Стратегия управления медицинскими услугами в медицинских информационных системах

To determine the strategy of service management in medical institutions, the article discusses the basic concepts associated with services, gives goal-setting, defines the roles, properties and attributes of medical services, gives recommendations for managing services through the HIS. Service management is considered on the example of HIS Interin PROMIS Alpha (Interin Technologies, Moscow). P u r p o s e . Develop a strategy for managing medical services, define goals and objectives for managing services. Analyze the role of information technology in the implementation of medical services in the free market. M a t e r i a l s a n d m e t h o d s . Models for maintaining a catalog of medical services are analyzed. The experience of service management in medical institutions based on the existing regulatory framework has been studied. The characteristics of medical services that determine the features of their economic accounting are analyzed. The role of MIS in providing analytical and control tools, as well as mechanisms for configuring business processes is determined. R e s u l t s . The methodology and stages of transition to a centralized model of maintaining a catalog of medical services have been developed. The tools for managing the production of medical services are described. F i n d i n g s . The most effective production management strategy in the MO is a centralized (organizational and methodological) model based on a single catalog of medical services, the ability to perform which is evidence of the maturity of the organization.

KEY PERFORMANCE INDICATORS OF INDUSTRIAL SAFETY OF ENTERPRISES

This article discusses the issues of assessing the level of industrial safety of enterprises in terms of the efficiency of industrial enterprises, requiring an increase in production efficiency, ensuring the efficiency of products and services by mastering the ways of effective production management, the achievements of scientific and technological progress.
 Purpose: The article discusses key performance indicators as methods of industrial safety of an enterprise and a tool for analyzing and evaluating the level of a company’s performance.
 Method, methodology of the work: The article used theoretical materials, economic and mathematical methods, statistical methods of analysis.
 Results: The most informative parameters were obtained, showing some aspects of the analysis of key performance indicators of industrial enterprises.
 Scope of the results: The results obtained can be successfully applied in different areas of the economy for different economic entities, it is possible to use both for young firms and for organizations with sufficient experience.

MANAGEMENT OF THE WORKPLACES BY THE FACILITIES OF OPERATIONS RESEARCH

The optimal location of workplaces plays an important role in the structure of occupational safety. The design of the workspace should ensure the optimal distribution of functions between person and machine in order to create safe working conditions, reduce the severity of work and the level of production injuries. Most often, workplace planning is carried out manually, by simple calculation, and then the rationality of workplace planning is evaluated, based on statistics of industrial accidents and occupational diseases, as well as indicators of labor productivity, for example, the ratio of compliance with norms. To solve the problem of optimal placement in the work mathematical models are built that can take into account various regulatory restrictions and are simple for further software implementation. It is proposed to choose the theory of φ-functions as a basis, which can be characterized as measures of proximity of objects. Thus, the set task of optimal placement of workplaces is reduced to the task of mathematical programming. The objective function determines the criterion of optimality – the minimization of the area or perimeter that will be occupied by the objects. This formulation of the problem is relevant because the use of the smallest production area, taking into account safety requirements, is an economic condition for effective production management. The constraint on the relative location of workplaces is set using φ-functions, which defines the decision domain. That, when formalizing restrictions, you can take into account all regulatory safety distances between workplaces, equipment, walls, etc. Thus, the work explores an approach that will allow automatic planning of the placement of a large number of technological objects, workplaces in accordance with occupational safety standards. Use of the software application, which can be implemented on the basis of the φ-functions apparatus, will significantly reduce the time of workplaces planning and increase its efficiency.

Problem Decomposition and Multi-shot ASP Solving for Job-shop Scheduling

AbstractScheduling methods are important for effective production and logistics management, where tasks need to be allocated and performed with limited resources. In particular, the Job-shop Scheduling Problem (JSP) is a well known and challenging combinatorial optimization problem in which tasks sharing a machine are to be arranged in a sequence such that encompassing jobs can be completed as early as possible. Given that already moderately sized JSP instances can be highly combinatorial, and neither optimal schedules nor the runtime to termination of complete optimization methods is known, efficient approaches to approximate good-quality schedules are of interest. In this paper, we propose problem decomposition into time windows whose operations can be successively scheduled and optimized by means of multi-shot Answer Set Programming (ASP) solving. From a computational perspective, decomposition aims to split highly complex scheduling tasks into better manageable subproblems with a balanced number of operations so that good-quality or even optimal partial solutions can be reliably found in a small fraction of runtime. Regarding the feasibility and quality of solutions, problem decomposition must respect the precedence of operations within their jobs and partial schedules optimized by time windows should yield better global solutions than obtainable in similar runtime on the entire instance. We devise and investigate a variety of decomposition strategies in terms of the number and size of time windows as well as heuristics for choosing their operations. Moreover, we incorporate time window overlapping and compression techniques into the iterative scheduling process to counteract window-wise optimization limitations restricted to partial schedules. Our experiments on JSP benchmark sets of several sizes show that successive optimization by multi-shot ASP solving leads to substantially better schedules within the runtime limit than global optimization on the full problem, where the gap increases with the number of operations to schedule. While the obtained solution quality still remains behind a state-of-the-art Constraint Programming system, our multi-shot solving approach comes closer the larger the instance size, demonstrating good scalability by problem decomposition.

Community-Based Local Wisdom Development : Strengthening Accounting and Production Management Skills “Batik Village New Normal Bogor”

Batik art which is an intangible cultural heritage native to Indonesia that can be developed based on the potential of local wisdom in each region. This activity is aimed at increasing the ability and providing understanding to the local community-based batik MSME group in managing simple finances and optimal production management. The method used in this activity is theoretical and concept training which is carried out face-to-face, mentoring and direct monitoring in the field by the resource persons. This activity is targeted to be able to increase the 2 (two) new normal batik business groups that have just been formed, able to implement an appropriate and good bookkeeping system in the operation of their business. And can also run an effective and efficient production management system, so as to be able to produce good batik products and have a competitive advantage compared to batik products that are already on the market.

Circular economy to ensure production operational sustainability: A green-lean approach

Satisfying the requirements associated with environmental concerns and resource efficiency in the manufacturing process has become necessary to realize effective production management. Specifically, manufacturers must identify novel working procedures or methodologies to enhance the resource efficiency and environmental friendliness of production processes. Green-lean production and a circular economy are promising schemes to achieve this goal. However, compared to green-lean management, the implementation of a circular economy in production operations remains relatively unclear. Several scholars have recommended the combination of the circular economy and green-lean concepts to bridge this gap, however, systematic methods remain to be developed. Considering this aspect, this study proposes a method that integrates green-lean solutions with the circular economy concept. The proposed method is applied in production operations through the principle of continuous improvement to enhance the environmental and resource performance aspects. The method includes three successive phases, which can not only help managers fully identify the opportunities for improvement but also provide managers with directions for improvement by introducing four strategy quadrants. The effectiveness and practicability of the proposed method are proven considering an industrial case of the assembly workshop of an automobile company. The proposed study can support enhance theoretical knowledge regarding the green-lean and circular economy concepts and demonstrates the implementation of a circular economy in the process of optimizing the production operation of manufacturing enterprises.

Optimization of Production and Inventory Control

Production and inventory management are two interconnected concepts that are crucial to the success of any physical product-driven organization. Production management consists of planning, coordinating, and regulating the manufacturing process to guarantee that things are produced effectively, on schedule, and in sufficient numbers. This process often entails managing production resources such as people, materials, and equipment to fulfill production targets while minimizing waste and increasing productivity. On the other hand, inventory management is the management of a company's stock of finished items, work in progress, and raw materials. It is concerned with ensuring that the appropriate quantity of inventory is available at the appropriate time to fulfill customer demand while reducing the expenses associated with surplus inventory. Effective production and inventory management are required for businesses to satisfy client demand, sustain profitability, and compete in the market. Businesses may cut costs, enhance productivity, and raise customer happiness by streamlining manufacturing processes and successfully controlling inventory levels.

Open-source Software Sustainability Models: Initial White Paper From the Informatics Technology for Cancer Research Sustainability and Industry Partnership Working Group.

BackgroundThe National Cancer Institute Informatics Technology for Cancer Research (ITCR) program provides a series of funding mechanisms to create an ecosystem of open-source software (OSS) that serves the needs of cancer research. As the ITCR ecosystem substantially grows, it faces the challenge of the long-term sustainability of the software being developed by ITCR grantees. To address this challenge, the ITCR sustainability and industry partnership working group (SIP-WG) was convened in 2019.ObjectiveThe charter of the SIP-WG is to investigate options to enhance the long-term sustainability of the OSS being developed by ITCR, in part by developing a collection of business model archetypes that can serve as sustainability plans for ITCR OSS development initiatives. The working group assembled models from the ITCR program, from other studies, and from the engagement of its extensive network of relationships with other organizations (eg, Chan Zuckerberg Initiative, Open Source Initiative, and Software Sustainability Institute) in support of this objective.MethodsThis paper reviews the existing sustainability models and describes 10 OSS use cases disseminated by the SIP-WG and others, including 3D Slicer, Bioconductor, Cytoscape, Globus, i2b2 (Informatics for Integrating Biology and the Bedside) and tranSMART, Insight Toolkit, Linux, Observational Health Data Sciences and Informatics tools, R, and REDCap (Research Electronic Data Capture), in 10 sustainability aspects: governance, documentation, code quality, support, ecosystem collaboration, security, legal, finance, marketing, and dependency hygiene.ResultsInformation available to the public reveals that all 10 OSS have effective governance, comprehensive documentation, high code quality, reliable dependency hygiene, strong user and developer support, and active marketing. These OSS include a variety of licensing models (eg, general public license version 2, general public license version 3, Berkeley Software Distribution, and Apache 3) and financial models (eg, federal research funding, industry and membership support, and commercial support). However, detailed information on ecosystem collaboration and security is not publicly provided by most OSS.ConclusionsWe recommend 6 essential attributes for research software: alignment with unmet scientific needs, a dedicated development team, a vibrant user community, a feasible licensing model, a sustainable financial model, and effective product management. We also stress important actions to be considered in future ITCR activities that involve the discussion of the sustainability and licensing models for ITCR OSS, the establishment of a central library, the allocation of consulting resources to code quality control, ecosystem collaboration, security, and dependency hygiene.

TECHNOLOGICAL REENGINEERING IN THE MANAGEMENT SYSTEM OF INNOVATIVE TRANSFORMATIONS

The article considers operations research methods and system analysis for solving dynamic production management problems related to increasing its flexibility. The most important elements characterizing the effectiveness of the management process are the state of the management object and the presence of certain production opportunities to change its state. The organization of effective production management in the process of innovative transformations leads to the need to consider the general scheme of managing the entire complex of works carried out during this period as a complex dynamic system, which at the stage of introducing innovations is not yet sufficiently adapted to production and technological transformations due to the wide variety of alternatives for implementing the functions of such a system. It is outlined that effective methods of system analysis have not yet been developed due to the complexity and diversity of the boundary conditions of the activities of various machine-building enterprises. However, the permanent nature of the innovative transformations of their production base allows drawing a conclusion about the perspective of the simultaneous application of the technological reengineering methodology for the management system. It is substantiated that the preliminary modeling when solving the tasks of managing the production process and performing specific works on technological rehabilitation should be built taking into account the provision of the necessary efficiency of the control system. This can ensure its technological rehabilitation. The mathematical model of the interrelationship of elements that are key to increasing the efficiency of the management system at the industrial enterprise that is conducting technological rehabilitation of its production base, and which are determined by a complex of functional management tasks, is proposed. Keywords: innovative transformations, process, management, organization, production base, parameters, project.

Estimating Production Metric for Ship Assembly Based on Geometric and Production Information of Ship Block Model

To secure technological competitiveness in shipbuilding and offshore industries, the continuous application and development of various technologies is essential. Efficient scheduling in shipyards is an important management task, whereby materials and manpower are allocated at the appropriate time and to the correct workspace. Although some large shipyards ensure effective scheduling and production management through simulations employing advanced technologies, most shipbuilding industries, including small- and medium-sized shipyards, continue to use an index based on past experiences. However, this legacy index, termed the basic unit, involves poor engineering logic; therefore, it does not appropriately reflect a shipyard’s working environment, which changes rapidly in response to technological developments. Although this has led to a demand for improvements in the basic unit, a clear solution has not been presented thus far. In this study, a method for calculating the man-hours required for assembly, which is the basis for preparing the basic unit, is proposed. First, the assembly process is analyzed, and individual activities involved in the assembly process are quantified and formulated into working hours, which is defined as a production metric. Based on a ship’s computerized block model, the geometric properties and production information required for calculating the metric are generated automatically as far as possible; this is to establish a convenient production metric calculation system. The proposed method features complete applicability in new shipyards through a customization. It also serves as a tool for predicting the metric of new ships or comparisons with those of existing ships.

New Approach for Quality Function Deployment Using Linguistic Z-Numbers and EDAS Method

Quality function deployment (QFD) is an effective product development and management tool, which has been broadly applied in various industries to develop and improve products or services. Nonetheless, when used in real situations, the traditional QFD method shows some important weaknesses, especially in describing experts’ opinions, weighting customer requirements, and ranking engineering characteristics. In this study, a new QFD approach integrating linguistic Z-numbers and evaluation based on distance from average solution (EDAS) method is proposed to determine the prioritization of engineering characteristics. Specially, linguistic Z-numbers are adopted to deal with the vague evaluation information provided by experts on the relationships among customer requirements and engineering characteristics. Then, the EDAS method is extended to estimate the final priority ratings of engineering characteristics. Additionally, stepwise weight assessment ratio analysis (SWARA) method is employed to derive the relative weights of customer requirements. Finally, a practical case of Panda shared car design is introduced and a comparison is conducted to verify the feasibility and effectiveness of the proposed QFD approach. The results show that the proposed linguistic Z-EDAS method can not only represent experts’ interrelation evaluation information flexibly, but also produce a more reasonable and reliable prioritization of engineering characteristics in QFD.