High Level Of Customization Research Articles

Empirical analysis of key operational characteristics of lean six sigma and Industry 4.0 integration

PurposeTo achieve changing customer demands, organizations are striving hard to embrace cutting-edge technologies facilitating a high level of customization. Industry 4.0 (I4.0) implementation aids in handling big data that could help generate customized products. Lean six sigma (LSS) depends on data analysis to execute complex problems. Hence, the present study aims to empirically examine the key operational characteristics of LSS and I4.0 integration such as principles, workforce skills, critical success factors, challenges, LSS tools, I4.0 technologies and performance measures.Design/methodology/approachTo stay competitive in the market and quickly respond to market demands, industries need to go ahead with digital transformation. I4.0 enables building intelligent factories by creating smart manufacturing systems comprising machines, operators and information and communication technologies through the complete value chain. This study utilizes an online survey on Operational Excellence professionals (Lean/Six Sigma), Managers/Consultants, Managing Directors/Executive Directors, Specialists/Analysts/Engineers, CEO/COO/CIO, SVP/VP/AVP, Industry 4.0 professionals and others working in the field of I4.0 and LSS. In total, 83 respondents participated in the study.FindingsBased on the responses received, reliability, exploratory factor analysis and non-response bias analysis were carried out to understand the biasness of the responses. Further, the top five operational characteristics were reported for LSS and I4.0 integration.Research limitations/implicationsOne of the limitations of the study is the sample size. Since I4.0 is a new concept and its integration with LSS is not yet explored; it was difficult to achieve a large sample size.Practical implicationsOrganizations can utilize the study findings to realize the top principles, workforce skills, critical success factors, challenges, LSS tools, I4.0 tools and performance measures with respect to LSS and I4.0 integration. Moreover, these operational characteristics will help to assess the organization's readiness before and after the implementation of this integration.Originality/valueThe authors' original contribution is the empirical investigation of operational characteristics responsible for I4.0 and LSS integration.

A practical simulation approach for the support of wire arc DED additive manufacturing systems design

Wire Arc Directed Energy Deposition (DED) is a subcategory of the DED Additive Manufacturing (AM) technology that is rapidly gaining popularity due to its potential to produce large-scale, complex metal parts while maintaining a lower cost and higher productivity and sustainability when compared with other AM technologies. Additionally, Wire Arc DED permits a high level of customization in terms of designing and implementing manufacturing systems. However, there are still important quality issues hindering wire Arc DED, along with limited simulation approaches that offer the necessary practicality, from an industrial perspective, to support the design of wire Arc DED manufacturing systems. Towards this goal, aiming to the minimization of the experimental cost and time, a simulation approach of wire arc DED is presented in this study. The model has been developed in COMSOL Multiphysics, allowing for a high level of customization, while maintaining practicality and ease of use, both in terms of implementation as well as computational cost. The modeling approach is analyzed, followed by the implementation of the methodology in a case study. Preliminary results are presented, discussed, and accompanied by suggestions for future research.

PROTO – A Customized Assistant To Optimize Personal Tasks

In today's interconnected world, the combination of technology and AI has become an essential part of daily life. AI-powered voice assistants have evolved into indispensable tools, seamlessly integrating technology into everyday tasks. This project demonstrates the development of a Customised Artificial Intelligence Assistant in Python, which was chosen for its extensive library set suitable for building AI applications. This assistant is designed to make computer-related tasks easier and more convenient for users. The assistant improves functionality and user experience by combining voice recognition, natural language processing, and external API integration, such as the OpenAI API. What distinguishes this assistant is its high level of customisation and extensibility, which allows users to tailor its behaviour and features to their specific requirements. These intelligent programmes use voice commands to understand human natural languages and complete tasks for the user. It can perform a variety of basic tasks, including launching applications, conducting searches without a web browser, playing music, and more, all by responding to voice commands. Furthermore, the assistant works seamlessly with popular tools and services, providing a user-friendly experience for both beginners and experts. The goal of this project is to improve users' productivity and efficiency in their daily computer tasks by combining accessibility, automation, and customisable features.

Enhancing sustainability in the production of cruise-ship modules through quality monitoring

Constructing cruise-ship hull is long, complex and requires relatively precise metal carpentry, welding and assembly operations. Timely detection and correction of anomalies is vital to the sustainability of the process, in terms of reducing production time and costs. This paper presents a novel statistical quality control (SQC) methodology for monitoring the workshop for the production of so-called “modules” within shipyards, i.e., roughly parallelepiped sub-assemblies of large dimensions (on the order of several tens of meters on each side), obtained through manual carpentry and welding operations. The proposed methodology adopts a standardized p control chart with samples of variable size, incorporating two elements: (i) it accounts for the high level of customization of modules, and (ii) it takes into consideration the measurement uncertainty associated with the large-volume metrology instrument employed for conformity verification (such as a state-of-the-art Leica RTC360 laser scanner), following the ISO 14253-1:2017 standard. A real-world case study at an Italian Fincantieri S.p.A. shipyard demonstrates its practical application.

Infill Density Effects on the Mechanical and Thermal Properties of Copper‐Plated 3D Printed Parts

AbstractFused Filament Fabrication (FFF) is a 3D‐printing technique that enables the production of complex geometries with a high level of customization at low cost. The poor mechanical properties of FFF‐printed parts often undermine the application of this technology for structural purposes. To overcome this limitation, a two‐step metallization method is performed to deposit a copper layer on the exterior of an Acrylonitrile–Butadiene–Styrene (ABS) substrate, using a non‐toxic and cost‐effective plating solution. Electroplating over the exposed grid infill, at various densities, is exploited to improve the load transfer between copper and ABS. The resulting samples are characterized mechanically and thermally, and finite element modeling simulations are used to better understand the characterization results. It is found that an infill of 50–60% provides the best compromise between mechanical performance and thermal conductivity because the infill density is low enough to allow copper penetration into the material to create a strong mechanical interlocking with ABS, yet high enough to create multiple conductive bridges through the thickness of the sample. This study demonstrates the effectiveness of electroplating as a post‐processing technique to simultaneously enhance the mechanical and thermal properties of FFF‐printed parts and provides insights into the optimal design parameters for achieving this goal.

Optimizing the material distribution method for automotive electronic switch production: A rigid and flexible approach

The lifecycle of automotive electronic switches is relatively short. The products exhibit a high level of customization. The assembly production demonstrates characteristics of high variety in small batch sizes and frequent production changeovers. Traditional delivery methods often result in issues such as excessive line-side inventory, residual material accumulation, and material management disorder. In this article, a reverse planning approach is adopted to logically analyze from the material demand side to the supply side. By integrating the concepts of push and pull production control, a just-in-time delivery sequencing model is designed. Furthermore, the model was validated based on production data from Company A. The aim is to reduce line-side inventory, improve delivery accuracy, shift from ensuring material supply to efficient supply, and enhance inventory turnover. The purpose of improvement is to achieve a 20% reduction in floor space occupied by the assembly workshop at the same production level, decrease line-side inventory (including raw materials, work-in-progress, and finished goods) by 30%, increase inventory turnover by 20%, reduce the working hours required for logistics personnel by 30%, and improve the accuracy of material deployment (including quantity and part number) from 92% to 99%.

When investors meet consumers: The roles and interactions of different backers in the crowdfunding market

AbstractBy harnessing the power of the crowd, crowdfunding has changed the way startup ventures, innovation‐minded entrepreneurs, and private individuals raise capital. Reward‐based crowdfunding is an established and attractive fundraising option for entrepreneurs with creative projects, while investment‐based crowdfunding has also gained popularity thanks to the progress of related regulations. Both types of crowdfunding are drawing a growing number of startups that seek funding opportunities, although backers on different types of crowdfunding platforms exhibit distinct motivations. Understanding the behavior and interaction of different types of backers is thus critical for a startup to launch a successful crowdfunding campaign across distinct platforms.To address this issue, we conduct a field study on a popular crowdfunding platform, where each campaign offered both reward‐ and investment‐based funding. Interestingly, we find a positive relationship between investor contributions in the early stage of the campaign and the likelihood of the campaign's success. Our empirical analysis reveals that investor–consumer interaction mediates the main effect of early investor contributions. Moreover, the positive main effect is stronger when a larger amount of project‐relevant information is released and when a higher level of customization (using price discrimination or product differentiation) is offered in reward‐based funding options. These results are consistent with several robustness checks. Our findings provide relevant managerial implications for entrepreneurs and valuable insights regarding platform design.

Efficacy and selectivity of tumor-treating field therapy for triple-negative breast cancer cells via in-house delivery device

PurposeTriple-negative breast cancer continues to be one of the leading causes of death in women, making up 7% of all cancer deaths. Tumor-treating electric fields are low-energy, low-frequency oscillating electric fields that induce an anti-proliferative effect on mitotic cells in glioblastoma multiforme, non-small cell lung cancer, and ovarian cancer. Little is known about effects of tumor-treating fields on triple-negative breast cancer and known research for tumor-treating fields only utilizes low (< 3 V/cm) electric field intensities.MethodsWe have developed an in-house field delivery device capable of high levels of customization to explore a much wider variety of electric field and treatment parameters. Furthermore, we investigated the selectivity of tumor-treating field treatment between triple-negative breast cancer and human breast epithelial cells.ResultsTumor-treating fields show greatest efficacy against triple-negative breast cancer cell lines between 1 and 3 V/cm electric field intensities while having little effect on epithelial cells.ConclusionThese results provide a clear therapeutic window for tumor-treating field delivery to triple-negative breast cancer.

Data-Driven and Machine Learning-Based Framework for Image-Guided Single-Cell Mass Spectrometry.

Improved throughput of analysis and lowered limits of detection have allowed single-cell chemical analysis to go beyond the detection of a few molecules in such volume-limited samples, enabling researchers to characterize different functional states of individual cells. Image-guided single-cell mass spectrometry leverages optical and fluorescence microscopy in the high-throughput analysis of cellular and subcellular targets. In this work, we propose DATSIGMA (DAta-driven Tools for Single-cell analysis using Image-Guided MAss spectrometry), a workflow based on data-driven and machine learning approaches for feature extraction and enhanced interpretability of complex single-cell mass spectrometry data. Here, we implemented our toolset with user-friendly programs and tested it on multiple experimental data sets that cover a wide range of biological applications, including classifying various brain cell types. Because it is open-source, it offers a high level of customization and can be easily adapted to other types of single-cell mass spectrometry data.

Radio resource allocation in a 6G D-OMA network with imperfect SIC: A framework aided by a bi-objective hyper-heuristic

In the sixth generation (6G) of mobile communication networks, radio resource allocation management (RRAM) systems must offer high levels of customization and sustainability in their operations. For this reason, this article proposes a framework that maximizes the quality of experience (QoE) of users of a 6G network that implements the delta-orthogonal multiple access (D-OMA) scheme as well as the system’s energy efficiency (EE), considering imperfections in successive interference cancellation (SIC) activities. The framework has two phases: in phase (a), a low-complexity heuristic was implemented in order to carry out the selection of base stations (BSs) and distribution of the electromagnetic spectrum slices to each communication device (CD); and in phase (b), a new bi-objective selection hyper-heuristic (SHH) performs the transmission power levels allocation. To evaluate the framework’s performance, we performed two tests: First, we evaluated the generalization capacity of our SHH with the isolated application of its constituent metaheuristics. Second, our hyper-heuristic was compared to other state-of-the-art transmit power allocation methods (TPLAMs) developed for non-orthogonal multiple access (NOMA) environments. For a fair comparison, all TPLAMs used the same heuristic for phase (a). As a result, the framework, in addition to providing high levels of QoE to network users, also presented low levels of failure probability as well as improved the average EE of the system.

IMPACT OF USE OF MANAGEMENT CONTROL SYSTEM ON STRATEGY IMPLEMENTATION OF HIGHER EDUCATION INSTITUTIONS IN GUJARAT

Use of Strategy is inevitable for success of any organisation and for the effective implementation of the strategy, it is important to have an effective management control system. Increasing number of Higher Education Institutes has given an objective to carry out the present research work on the strategies implemented by the Higher Education Institutions and as far as like other organizations, strategies implementation of the Higher Education Institutions is concerned, it is affected by the Use of Management Control Systems. The present study has been carried out with a view to study impact of Use of Management Control System on Strategy Implementation of the Higher Education Institutions in Gujarat. For the accomplishment of the objective the primary data with the help of the questionnaire has been collected from the Heads of the Higher Education Institutions. It is hypothesised for the study that there is significant impact of Use of Management Control System on the Strategy Implementation of the Higher education institutions in the state of the Gujarat. The study found that Use of Management Control System in Higher Education Institutions in state of Gujarat led to positive impact on strategy implementation focus. It was found that the use of better management control system in Higher Education Institutions led to not only better implementation of strategy but also decentralization of strategies to university executive members with a view to facilitate customization of services which resulted into high level of customization in the design and delivery of programs.

Developing a more engaging safety training in agriculture: Gender differences in digital game preferences

Digital games have been effectively used in different working sectors as an occupational safety training method but they are still overlooked in agriculture, despite the high hazardousness of this industry. At the same time, the gender issue is becoming more and more relevant both in the digital game and agricultural fields because of an increasing number of females, both among the agricultural operators and the game players . Based on these considerations, our study aimed at investigating gender differences in the preference for different game characteristics to point out which aspects of a new game for safety training purposes in agriculture may appeal to both male and female operators and which aspects need instead a careful design and high levels of customization, to be equally appreciated by both genders. An online questionnaire was administered to a group of Italian Agricultural Science university students (N = 137, 65% males and 35% females) to investigate their game preferences, in terms of game characteristics, genre and graphic style. Some clear differences (in tasks, quests, rules, and goals, colors and variety), and similarities (in graphics, drama, better rewards and game genre) emerged in males' and females' preferences. Based on these results, some practical guidelines are provided for the design of a gamified safety training tool which can appeal to and be considered engaging by both genders.

Implementation of Strategies in Management of Change To Achieving Quality Levels of Service to Consumers (Case Study on Shopee Application Company)

Huge business opportunities such as product sales and online service provision and revenue growth for companies such as e-retailers are primarily due to their easy and interactive nature, lower costs, and high level of customization and personalization for customers. This research is intended to analyze service quality and consumer satisfaction of Shopee e-commerce application users. The purpose of this study is to be able to analyze how the strengths, weaknesses, opportunities and threats of using the shopee online store are. The research conducted is qualitative. The data collection using the distribution of questionnaires. Many consumers complain about the cycle of service and satisfaction levels in the Shopee application, both directly and indirectly. As it is known that making changes is not an easy thing for organizations, because all systems or some systems that will be changed automatically, members of the organization must also adapt to things that are not necessarily well received, therefore in the process of change there needs to be good management. whether done by the leader of the Shopee Application, there are things that must be done strategically in overcoming resistance well to ensure that a change will go well. So there is a lot that must be prepared before making changes, to improve the quality of service to consumers again.

Overview of the Uncertainty and Supply Chain Risk in Vietnamese Garment and Textile Firms: The Moderating Role of Supply Chain Flexibility in Risk Mitigation

To stay competitive in the market, firms are forced to offer high levels of customization and product offerings, which leads to high uncertainty in the supply chain. Consequently, in uncertain environment, firms would face the risk of supply disruptions, production, and delivery delays, resulting in poor operational performance. This paper aims to analyze and review the literature on operational uncertainty and risks in the supply chain that enterprises face. On that basis, the study outlines research gaps and future research needs. Keywords: Supply chain risk; Environmental uncertainty; Supply chain flexibility DOI: 10.7176/JESD/13-7-01 Publication date: April 30 th 2022

Scheduling para Manufatura Aditiva: uma revisão da literatura

Abstract: Advancements in production technologies and materials have facilitated the use of additive manufacturing (AM) (i.e., 3D printing) in the large-scale production of finished products with high level of customization, simplification of the factory floor, and fast delivery. Production sequencing is a well-established topic in this research area; however, its application to an AM environment suffers from specific issues that are yet to be explored. This paper presents a systematic literature review for mapping the state-of-the-art production sequencing methods in AM and for discussing the content of 26 articles published in magazines between 2017–2020. The main mathematical models, algorithms adopted for their solution, and main characteristics of computational experiments performed in these articles are identified; the results indicate that some characteristics of the problem can still be included in these models, such as the possibility of outsourcing and technology restrictions, which are yet to be explored in the literature. Further, authors observed the need for more robust computational experiments to better evaluate the proposed solutions.

Purpose-Built Immunoinformatics for BcR IG/TR Repertoire Data Analysis.

The study of antigen receptor gene repertoires using next-generation sequencing (NGS) technologies has disclosed an unprecedented depth of complexity, requiring novel computational and analytical solutions. Several bioinformatics workflows have been developed to this end, including the T-cell receptor/immunoglobulin profiler (TRIP), a web application implemented in R shiny, specifically designed for the purposes of comprehensive repertoire analysis, which is the focus of this chapter. TRIP has the potential to perform robust immunoprofiling analysis through the extraction and processing of the IMGT/HighV-Quest output, via a series of functions, ensuring the analysis of high-quality, biologically relevant data through a multilevel process of data filtering. Subsequently, it provides in-depth analysis of antigen receptor gene rearrangements, including (a) clonality assessment; (b) extraction of variable (V), diversity (D), and joining (J) gene repertoires; (c) CDR3 characterization at both the nucleotide and amino acid level; and (d) somatic hypermutation analysis, in the case of immunoglobulin gene rearrangements. Relevant to mention, TRIP enables a high level of customization through the integration of various options in key aspects of the analysis, such as clonotype definition and computation, hence allowing for flexibility without compromising on accuracy.

Defect prediction models to improve assembly processes in low-volume productions

Assembly processes in low-volume productions, i.e., single-units or small-sized-lots, are often characterized by a high level of customization and complexity. As a consequence, the scarcity of historical data and the difficulty in applying standard statistical techniques make process control extremely challenging. Accordingly, identifying effective diagnostic tools plays a key role in such productions. This paper proposes an innovative method for identifying critical workstations in assembly processes based on defect prediction models. Starting from the level of complexity in terms of assembly process and design, the method allows identifying the workstations whose defectiveness deviates, at a certain confidence level, from the predicted average value. Once the causes leading to significant nonconformities have been detected, appropriate corrective actions may be promptly undertaken to improve the process. An example of implementation of the method in wrapping machines production is presented and discussed.

Review and modification of DFA2 methodology to support design for automatic assembly (DFAA) in the maritime industry

DFA2 refers to a set of design rules introduced by S. Eskilander in his doctoral thesis[3] as a method to help design products for automatic assembly. In this method, design rules are used to assign an index to a particular design which can then give an indication of the suitability of that product/module to be assembled automatically. However, this methodology is based on a general perspective and is not fully suitable for the needs of every industry. This article reviews the methodology in the context of the maritime industry in Norway after studying a typical product offering from a maritime company. Based on the review, shortcomings of the DFA2 are realized and new design rules are proposed to be added to the original method. Additionally, this paper tries to prioritize the design rules based on certain criteria. This study suggests that the DFA2 methodology is customizable to meet the needs of any particular industry or organization. To achieve a high level of customization, a more detailed study of different product offerings from any individual company or industry is required.

Options-based Planning for Mass-Customization: A Simulation-Optimization Model

Increasingly, customers expect products highly customized with reduced lead-times. Additionally, intense geopolitical, economic and regulatory uncertainties render long lead-times increasingly risky for both equipment suppliers and customers alike. This article presents a mass customization model called optionsbased planning (OBP) which is better adapted to complex market realities than legacy production models. A discrete event simulation examines the performance of the new model compared to legacy production strategies. Under conditions of high market turbulence (i.e. trade wars, pandemics, etc.), the new model allows shorter customer lead-time while maintaining the high level of customization expected of highly valued capital equipment.

Attribute-based encryption and sticky policies for data access control in a smart home scenario: a comparison on networked smart object middleware

Regulating the access to the Internet of Things (IoT) network’s resources is a complex-prone task, which requires to pay a great attention on how policies are defined, shared, and enforced. The present paper considers the specific context of a smart home, which represents one of the main IoT application domains, and it focuses on two solutions proposed in the literature to cope with the aforementioned issues. On the one side, approaches based on attribute-based encryption (ABE) allow one to encrypt data for multiple recipients, in such a way that only those recipients whose attributes satisfy a given access policy can decrypt afterward. ABE guarantees a high level of customization due to the variety of attributes which can be defined, and it is also flexible enough to be adapted to different kinds of scenarios. On the other side, approaches based on sticky policies allow to attach an access policy directly to the data itself, and to employ a trusted authority to evaluate and enforce the policy itself. Sticky policies also guarantee a highly distributed and customizable enforcement of access control rules. In this paper, we compare the advantages and the drawbacks in terms of performance and robustness of such two techniques by means of their integration within the prototype of an IoT middleware, named networked smart object. Hence, the effectiveness of the presented solutions is validated by means of a real test-bed in the smart home scenario, in terms of storage occupancy, CPU load, and data retrieval delay. The final goal is to reveal the best approach to be used depending on the application’s requirements.