Industrial Example Research Articles

Особенности проектного персонала в сравнении с операционным: практический анализ причин различий

This study examines the key differences between project management professionals and operational staff in modern organizations, focusing on the industrial construction sector. The research aims to identify the practical factors underlying the distinct competencies, motivational drivers, and organizational approaches essential for effective project management. Using a comparative analysis based on industry examples and professional insights, the study reveals that success in project management is closely linked to specific competencies. These include the ability to integrate interdisciplinary knowledge, tolerance to uncertainty, and strategic long-term planning skills. Such competencies are primarily developed through involvement in complex projects with unique objectives, requiring cross-functional collaboration and adaptive management techniques. The research also explores how organizational factors, including budget responsibility, dynamic work environments, and flexible employment structures, contribute to the specialized nature of project management roles. These elements often necessitate higher qualifications and, consequently, different compensation structures for project management professionals. The findings highlight the importance of recognizing these distinctions in project management practices, team composition strategies, professional development programs, and motivational frameworks. This study contributes to the evolving field of project management by offering practical guidelines for organizations seeking to enhance their project execution capabilities and competitiveness as the use of project-based approaches in industrial construction continues to expand.

Forging Impactful DEI Collaborations: Aligning on Vision and Fostering Mutual Comprehension

This research brief explores the key principles and strategies for building successful diversity, equity, and inclusion (DEI) partnerships that are grounded in a shared vision and a deep appreciation for the diverse perspectives and experiences within an organization. The article emphasizes the importance of fostering a shared vision that inspires action and aligns cross-functional efforts, as well as cultivating mutual understanding through active listening, open dialogue, and psychological safety. Drawing on practical industry examples from the technology and healthcare sectors, the brief demonstrates how organizations can unlock the full potential of their diverse workforce and drive sustainable, impactful change by adopting a holistic, people-centric approach to DEI. The conclusion underscores the critical role of shared vision and mutual understanding in enabling successful DEI partnerships that contribute to long-term organizational success.

Scaling for Success: Organizing for Rapid Growth

The article examines the critical elements leaders must address to successfully scale a startup company without losing control or efficiency. As a startup grows rapidly, it must evolve its organizational structure, processes, and culture to support expansion. The article outlines key strategies, including departmentalization to gain focus and specialization, implementing strong communication channels to prevent silos, aligning hiring with strategic goals, streamlining the hiring process, and cultivating a values-driven culture that is maintained through rapid growth. It also emphasizes the need to continually refine the organization, such as iterating department models and enabling internal mobility, to sustain strategic alignment and agility. Drawing on research and industry examples, the article provides a comprehensive framework for how startups can structure their operations to maximize the opportunities of scaling while mitigating the risks of uncontrolled growth.

Bioeconomy innovation within traditional value chains: the example of the sugar industry in three European regions

Bioeconomy innovation within traditional value chains: the example of the sugar industry in three European regions

A multivariate finite horizon production control chart for monitoring the food production process

ABSTRACT Finite horizon production (FHP) processes are prevailing in the food industry. However, monitoring these multivariate FHP processes poses a significant challenge for statistical process control, primarily due to inadequate information about the distribution of multivariate observations. In this paper, a multivariate FHP (MFHP) control chart is proposed to monitor the food production processes with a limited number of reference samples, where the statistic of the proposed chart is derived from the distance from the monitored samples to support vectors of a support vector machine (SVM) classifier. The control limit of the statistic is designed from a conditional perspective, taking into account the variability generated across different reference samples. An enhanced cache-optimized sequential minimal optimization algorithm (ECSMOA) is proposed to speed up the computation of the control limit. Extensive numerical analysis indicates that the proposed chart is more effective and robust in preserving a desired in-control performance and guaranteeing an out-of-control performance. Particularly, the variance of performance measures was reduced by approximately 87.09 % . Finally, an industrial example based on whole wheat bread production processes is given to demonstrate the implementation of the proposed chart.

Advancing Business Intelligence with SAP Analytics: A Comprehensive Analysis

SAP Analytics is a cutting-edge suite of tools enabling data-driven decision-making for modern enterprises. This paper explores SAP Analytics comprehensively, emphasizing its core features, integration with enterprise resource planning (ERP) systems, predictive analytics capabilities, and its role in diverse industries. Drawing on an extensive review of recent literature, case studies, and industry examples, the article also highlights implementation challenges and presents strategies to address them. Emerging trends such as artificial intelligence (AI), Internet of Things (IoT) integration, and blockchain applications in analytics are discussed to provide a forward-looking perspective. This paper is intended as a resource for business professionals, analysts, and researchers seeking to maximize the value of SAP Analytics

Navigating through uncertainties: coordinating digital transformation in international manufacturing networks

PurposeCoordination of digital transformation within globally dispersed factories belonging to international manufacturing networks (IMNs) is essential for competitiveness. This paper explores how digital transformation necessitates changes in the coordination of IMNs.Design/methodology/approachA case study is conducted with three Swedish manufacturing companies, thus adding to the limited empirical research covering the examined research field. Data analysis uses the technology-organization-environment (TOE) framework.FindingsThe results highlight 15 digital transformation attributes linked by intermediate themes to 13 changes in the coordination of IMNs and provide concrete industry examples. Four major themes emerged as significant in the coordination of IMNs: increased speed of technology development and rollout, amplified emphasis on a global mindset, increased need to adapt the organizational structures to enable collaboration and a higher degree of uncertainty.Originality/valueAlthough coordination of IMNs is acknowledged as directly related to competitive advantage, the ways digital transformation necessitates changes in the coordination of IMNs have been missing in contemporary research. This research decreases this omission.

Auto-tuning of filtered proportional-integral-derivative controller for industrial processes under routine operating conditions.

In general, auto-tuning implementation of PID controllers relies on dual controllers, exciting/identification experiments or some prior knowledge on the process and hence the considerable cost on auto-tuning implementation occurs. To deal with such a problem, a new auto-tuning scheme of the FPID controller is developed for minimum variance tasks under routine operating conditions in which the closed-loop system is running without any external excitation other than natural disturbances. This paper reveals that the stochastic disturbance model can be uniquely determined from the first several terms of the impulse response coefficients of the closed-loop system when the precondition on the time delay and the order of the disturbance model is satisfied. Based on the closed-loop non-parametric model (in terms of impulse response coefficients) that is estimated online by utilizing the one-shot closed-loop output data, the disturbance model is estimated by solving an optimization problem and hence the plant model is obtained. Subsequently, the new parameter set of the FPID controller is updated online by solving an optimization problem with respect to the H2 norm of the resulting closed-loop transfer function. The benefit of the proposed scheme over the existing auto-tuning methods is the cost saving of the auto-tuning implementation due to the following facts: i) it does not rely on dual controllers or identification/exciting experiments; ii) it does not require prior knowledge of the process. The effectiveness of the proposed scheme is illustrated in terms of output variance index by numerical cases and industrial examples.

Nonlinear Dynamic Analysis Using Harmonic Balance Method

There is a high demand for nonlinear structural dynamics in implicit Finite Element Analysis (FEA). Although such methods are available, there are several obstacles to use them daily. One is their extreme and unpredictable computation time, which makes it often impossible to get results in time. Another point is the restriction of the methods to the time domain, which is often in contrary to the usual design rules based on frequency domain results. The Harmonic Balance Method (HBM) is a solution for an important sub-class of analysis cases, which resolves the two mentioned obstacles. As a starting point, we define HBM as a frequency response analysis with local nonlinearities. This allows to solve contact problems or mounting problems with nonlinear force-deflection curves. The primary results of HBM are in frequency domain. For all calculated frequencies, a solution in time domain is also available for a periodic response. A simplified radiator is used as industrial example. To prove the validity of HBM, a comparison with a linear frequency response analysis is performed, which shows same results. Then, rubber bushes and contact are added to the model as nonlinearities. Key results of stress and fatigue are presented, and the computation times are analysed to demonstrate the feasibility of the HBM implementation for applications in research and industry. All simulations are performed with the FEA software PERMAS, which contains the HBM among many other analysis methods in structural dynamics.

Advancements in Abrasive Waterjet Cutting Technologies: A Comprehensive Overview and Future Prospects in the Manufacturing Industry

The purpose of this article is to provide a comprehensive overview of the latest trends in abrasive waterjet cutting technologies and their current state of the art. The article will explore the basic principles of abrasive waterjet cutting and the process advantages and application fields. Additionally, the article will discuss the latest developments in abrasive waterjet cutting technologies, including advancements in abrasive waterjet systems, automation and control systems, and nozzle materials. It will also highlight the most advanced systems currently available and their features and capabilities, as well as provide examples of industries with specific applications that are currently using abrasive waterjet cutting technologies. Finally, the article will discuss potential future developments in abrasive waterjet cutting technologies and their potential to enhance cutting precision, speed, and efficiency, and lead to new applications. Overall, this article aims to provide a comprehensive understanding of abrasive waterjet cutting technologies and their importance in the manufacturing industry.

Leading with Courage and Integrity in Complex Times

Abstract: In an era of heightened complexity and volatility, the need for courageous and principled leadership has never been more pressing. This article explores the essential qualities of courage and integrity, and the strategies leaders can employ to cultivate these attributes within their organizations. Grounded in empirical research from the fields of positive psychology, organizational behavior, and leadership studies, the brief outlines practical approaches for fostering psychological safety, embracing vulnerability, prioritizing continuous learning, and making ethical decisions. Through industry examples from the pharmaceutical, financial services, and technology sectors, the brief demonstrates how leaders who embody courage and integrity are better equipped to navigate complex challenges, inspire their teams, and position their organizations for long-term success. By implementing the research-backed strategies presented here, leaders can empower their organizations to thrive in an ever-changing business environment.

Making the Most of Workplace Missteps

This article provides a comprehensive framework for turning workplace mistakes into opportunities for growth and strengthening one's organizational reputation. Drawing on scholarly literature and the author's extensive consulting and academic research experience, the brief outlines a step-by-step approach including quickly acknowledging the error, analyzing root causes, developing a thoughtful remediation plan, communicating transparently with affected parties, and reflecting on lessons learned to incorporate into one's professional practice going forward. Written in a conversational, practitioner-focused style with real-world industry examples, the framework empowers professionals to navigate mistakes with courage, humility, and a commitment to continuous improvement, positioning themselves as trusted, adaptable, and indispensable members of their organizations.

Inspiring Purpose: How Defining a Clear WHY Drives Organizational Success

This article builds a robust business case for purpose-driven leadership, demonstrating through research and industry examples how effective leaders who clearly articulate an inspiring organizational purpose can drive significantly higher employee engagement, customer satisfaction and loyalty, as well as superior long-term financial performance - with purpose-oriented companies consistently outperforming peers. The paper outlines a comprehensive framework for understanding leadership as a process of influencing a group towards common goals, and highlights how defining a compelling "why" or purpose is central to this, going beyond just holding formal authority. Practical strategies for implementing purpose-driven leadership are provided, using examples from companies like Patagonia and Microsoft to illustrate the positive outcomes, as the paper makes a compelling argument that in today's interconnected world, leaders who can inspire stakeholders with a clear and motivating sense of purpose are best positioned to maximize organizational potential and achieve sustained success.

Catalysts for Growth at Work: Unlocking Human Potential through Empowering Workplace Cultures

This practitioner-oriented research brief explores key catalysts for cultivating growth, engagement, and well-being in the workplace. Drawing from literature reviews and the author's consulting and research experience, autonomy, collaboration, and meaningful work are identified as potent drivers of individual and organizational performance when strengthened in work cultures and designs. Each catalyst is defined and supported by academic research outlining their positive impacts on motivation, learning, innovation, stress reduction, and more. Practical strategies are then shared for how forward-thinking companies can enhance autonomy through job crafting, remote work, and distributed leadership. Collaboration is examined through sociocratic governance, internal social platforms, and open-book management approaches. The concept of meaningful work is unpacked and strategies like communicating social impact, allowing volunteerism, and highlighting tangible outcomes are presented. Specific industry examples also bring each concept to life. Overall, the brief argues that by optimizing these autonomy, collaboration and meaning catalysts, organizations empower happier, healthier employees better able to achieve their innate potential and drive unprecedented business success.

Driving Employee Engagement through HR Automation

This article explores how human resources can leverage automation to drive employee engagement. Drawing on both scholarly research and practical industry examples, the article outlines the key benefits of HR automation, including its ability to streamline administrative processes, enhance the employee experience, and free up HR professionals to focus on more strategic, engagement-driven initiatives. The articles covers specific use cases where automation can have the greatest impact, such as onboarding, performance management, learning and development, and HR service delivery. It also addresses the common barriers to implementing HR automation and provides strategies for overcoming them through effective change management. Finally, the brief examines the future of HR automation and its potential to transform employee engagement through emerging technologies like artificial intelligence and predictive analytics. The aim is to provide HR practitioners with a comprehensive understanding of how to harness the power of automation to cultivate a more engaged and productive workforce.

Applications of microfluidics in mRNA vaccine development: A review.

The transformative potential of microfluidics in the development of mRNA vaccines is explored in this review, highlighting its pivotal role in enhancing easy-to-use functionality, efficacy, and production efficiency. Moreover, we examine the innovative applications of microfluidics in biomedical research, including its contribution to the rapid and cost-effective synthesis of lipid nanoparticles for mRNA delivery and delve into the advantages of mRNA vaccines, such as targeted delivery and controlled expression. Furthermore, it outlines the future prospects of microfluidic devices, their cutting-edge examples in both research and industry, and the potential to revolutionize vaccine formulation and production. The integration of microfluidics with mRNA vaccine development represents a significant advancement in public health and disease prevention strategies.

Assessing the role of artificial intelligence in enhancing customer personalization: A study of ethical and privacy implications in digital marketing

Technological evolution, especially in artificial intelligence (AI), has significantly changed digital marketing, specifically customer-targeted experience. Machine learning, recommendation systems, and predictive analytics have made it possible for enterprises to personalize content, products, and services, among other things, on a very large scale. Nevertheless, all these advances have come with large ethical and privacy concerns that are yet to be met. This paper discusses how AI can enhance customers' personalization to analyze the moral and privacy considerations involved. The research examines how machine learning marketing strategies work in the digital environment and real-life examples of organizations that successfully implement these approaches and potential issues. It highlights how individuals might buy more products and make businesses more profitable with customized advertising techniques. However, the paper also describes the moral problems of AI that use personal data without permission, artificially intelligent algorithms that affect decision-making, and artificial intelligence decision-making. At the same time, its work has yet to be well known. The paper looks into privacy risks like data breach incidents, privacy violations, GDPR, and CCPA. This paper adopts an exploratory case study research design as it gathers academic papers, industry examples, and expert opinions to present a balanced view of the effects of AI. Based on the research, conclusions can be drawn that great opportunities AI opens for personalization should be met with safety considerations and working ethical guidelines. In the end, the paper presents guidelines that should help businesses integrate trust and compliance into creating and using AI technologies.

Gambling outlets as agents of local area disorganization: Crime and local institutions, the case of the UK

Amid growing public and policy concerns there is a great need for a systematic analysis of the relationship between commodity industries and social disorganization. Using data from the ONS, the UK Census, the UK Police Street-level Crime Dataset, and the POI Ordnance Survey, we analyse the association between gambling outlets as an example of a commodity industry and crime events across England and Wales and explore the possibility of a heterogeneous effect dependent upon the level of deprivation and residential stability of an area. Our findings show that gambling outlets are significantly and positively associated with different types of crime even when controlling for other businesses, the areas’ demographic and socio-economic characteristics. Small businesses provide distinctive shielding effects – in areas of high density of small business owners, there is no significant correlation between crime types and gambling density. Our results have significant policy implications.

A novel framework for optimizing job rotation schedules across industries

Implementing job rotation (JR) can yield positive or negative impacts depending on the firm characteristics and industry type. As a result, a generic framework for its implementation is difficult to develop and presently does not exist in literature. Existing models/frameworks have limited application as they are either too specific or generic, but imprecise. Consequently, managers often rely on their intuition to develop JR schedules which sometimes leads to suboptimal/unwanted outcomes. In this article, we propose a generic JR framework, which can be used by managers to develop optimal JR schedules in firms across many industries, such as IT, manufacturing, banking, medical, construction, chemical, aviation, etc. The proposed framework contributes to theory by addressing important questions, such as when to implement JR, and how to quantify some of its most important impacts. We also demonstrate the utility of the proposed framework through an illustrative industrial example.

Transforming Supplier Audits with AI: A Risk-Based Approach in Medical Devices

The medical device industry, highly regulated and sensitive to quality standards, relies on rigorous supplier audits to ensure compliance and mitigate risks. However, traditional supplier audits are often resource-intensive, inconsistent in quality, and lack a clear focus on the most critical risk factors. This paper explores how Artificial Intelligence (AI) can revolutionize the supplier audit process by enabling a risk-based approach that enhances accuracy, efficiency, and regulatory compliance. AI technology, with its advanced data processing, predictive analytics, and machine learning capabilities, can analyze vast amounts of supplier data in real-time, generating risk scores that prioritize high-risk suppliers for more frequent and thorough audits. This shift allows medical device companies to better allocate resources, focusing on high-impact areas and enhancing overall supply chain security. By considering factors such as supplier compliance history, product criticality, regional compliance laws, and performance trends, AI provides a dynamic and data-driven assessment model that minimizes the reliance on subjective audit practices. The paper introduces an AI-powered risk-based audit framework specifically tailored for medical device companies. This framework utilizes a multi-faceted AI-driven risk scorecard, categorizing suppliers by risk levels (high, medium, low) and enabling targeted audit strategies. It also demonstrates how AI can process a wide array of audit-related data inputs—such as supplier compliance, regional geopolitical risks, supply volume, and product criticality—to generate a holistic and accurate risk assessment. Through case studies and industry examples, this research underscores the advantages of integrating AI into supplier audit processes, highlighting cost savings, improved compliance outcomes, and reduced risk of quality issues or product recalls. Furthermore, it examines future trends and ethical considerations of AI in supplier audits, advocating for industry-wide adoption of AI-powered tools to support more efficient and effective supplier management. This paper concludes that adopting a risk-based, AI-driven audit approach in the medical device sector not only supports regulatory compliance but also builds resilience within the supply chain, creating a safer and more efficient landscape for medical device production.