Industrial Case Research Articles

Excelzyme: A Swiss University-Industry Collaboration for Accelerated Biocatalyst Development.

Excelzyme, an enzyme engineering platform located at the Zurich University of Applied Sciences, is dedicated to accelerating the development of tailored biocatalysts for large-scale industrial applications. Leveraging automation and advanced computational techniques, including machine learning, efficient biocatalysts can be generated in short timeframes. Toward this goal, Excelzyme systematically selects suitable protein scaffolds as the foundation for constructing complex enzyme libraries, thereby enhancing sequence and structural biocatalyst diversity. Here, we describe applied workflows and technologies as well as an industrial case study that exemplifies the successful application of the workflow.

A data-driven approach toward a machine- and system-level performance monitoring digital twin for production lines

Efficient performance monitoring in production systems holds paramount importance as it enables organizations to optimize their manufacturing processes, enhance productivity, and maintain a competitive edge in the market. Typically, machine and system level performance monitoring systems are investigated independently, whereas an integrated approach that considers both levels can offer valuable insights and benefits. This paper introduces a data-driven approach for evaluating and improving the performance of production lines by monitoring the performance of both individual machines and their interactions as a system. The approach begins with a rigorous methodology for classifying machine states recorded by the Manufacturing Execution System (MES) into finer-grained substates, enabling a comprehensive analysis of machine cycle time variability. Subsequently, these substates are leveraged as a foundation for constructing performance monitoring models at both the machine and system levels, employing probabilistic automata for the machine level and logistic regression for the system level. The system-level performance monitoring model is constructed to predict a Flow metric that enables the prediction of abnormal behaviors and deviations from production targets. This data-driven approach serves as a foundational ingredient of a system-level digital twin, designed to provide production lines with insights that enable proactive implementation of measures aimed at optimizing overall manufacturing efficiency. Through an industrial test case from the automotive industry, the results demonstrate the capability of performance monitoring, capturing errors within confidence intervals, and establishing predictive cause-and-effect relationships between machines within the production system.

Exploring brand equity assessment within consumer perception. Case of the jeans industry

Exploring brand equity assessment within consumer perception. Case of the jeans industry

The Role of Threat Intelligence in Enhancing Cybersecurity Posture

Organizations confront more complex and persistent cyberattacks in the quickly changing cyber threat landscape of today. Through the provision of actionable insights on emerging threats, adversary tactics, and vulnerabilities, cyber threat intelligence (CTI) becomes an increasingly important component in strengthening the cybersecurity posture of organizational networks. The importance of CTI and its useful uses in enhancing cybersecurity defences are examined in this research study. It explores the several kinds of threat intelligence, methods for compiling and evaluating threat information, and proactive steps that businesses may take to make the most of CTI. This study emphasizes the significance of incorporating CTI into cybersecurity plans to more effectively identify, prevent, and respond to cyber attacks through a thorough review of industry practices and case studies. Organizations may improve their defences against cyberattacks and enhance vital assets and data by comprehending the role that CTI plays in cybersecurity.

A Samsung production system-based approach to improve manufacturing process management in Vietnamese firms

Today, more and more Vietnamese firms consider continuous improvement as the best way to increase their manufacturing capability. This paper aims to illustrate the effectiveness of manufacturing processes management from the Samsung production system (SPS) approach when it was implemented to improve capability of existing production process in Vietnamese firms. The paper is a combination of descriptive and field research to demonstrate how SPS principles are appropriate for five real industry cases in particular and all Vietnamese manufacturing companies in general. In five cases, the usage of SPS-based tools has turned out to be fruitful. They solved problems of continuous improvement management in Vietnamese firms and created significant achievements in quality improvement and productivity increase. The paper investigates the core value of Samsung’s continuous process improvement. The way that Samsung has used to improve quality and profitability simultanously can be adapted by manufacturing companies.

Designing a green-resilient closed-loop supply chain to preserve business continuity under interrelated disruptions (a case study of the automotive battery industry)

Improving profitability, implementing the recycling cycle to reduce resource consumption, and managing interrelated disturbances to maintain business continuity are important issues for supply chain management. Accordingly, this study proposes a multi-objective optimization model to design a green-resilient closed-loop supply chain considering pricing decisions under multiple interrelated disturbances. Herein, the fuzzy c-means clustering method is employed to lessen probable scenarios and cluster main suppliers and target markets to reduce mathematical complexity. The multi-objective model is solved by adopting the improved augmented ε-constraint method to achieve the minimum total cost, total environmental impact, and network non-resiliency. The mixed uncertainty is coped with by developing a novel robust optimization method. Finally, an automotive battery manufacturing industry case study is applied to the model. The results reveal that the mutual effects of disturbances intensify the deterioration of objective functions. Also, the dynamic pricing of products reduces the financial vulnerability of the supply chain.

The transformation of digital strategy and value creation in omnichannel organisations: the case of the gambling industry

ABSTRACT Digital transformation strategy (DTS) involves redesigning various organisational operations to encompass digital technologies and achieve business objectives. In this study, we explored digital strategy and value creation shifts in omnichannel organisations that aimed to deliver seamless online and on-premises (dual-mode) customer experiences. Using comprehensive data on the gambling industry, we focused on the long-term effects of dynamic relationships among multiple DTS events over time. Building on digital strategy and value-creation theory, we observed and analysed organisational changes linked to technological shifts in omnichannel organisations during turbulent times and disruptions. Herein, we discuss the balance between online and on-premises service channels in terms of a DTS pathway, viewing it as a dual-mode value-creation process. By exploring this dual-mode value-creation process, we contribute to DTS theory and omnichannel operations. Furthermore, we enhance theory by unveiling the impact of shifting digital strategy perspectives on the transformation of omnichannel organisations in dynamic and disruptive business environments. We also present strategic propositions for planning and realising DTS requirements for omnichannel service providers in a broad context.

Resilience-oriented approach of dynamic production and maintenance scheduling optimisation considering operational uncertainty

ABSTRACT One of the main challenges in operating multistate manufacturing systems (MMSs) is maintaining stable and robust production against various disruptions. Therefore, an urgent need exists for an operation and maintenance (O&M) method that optimises MMS resilience, i.e. the capability of withstanding or recover from disruptions of various sources. Consequently, this study proposes an integrated resilience-oriented production and maintenance scheduling approach for MMSs. This approach enhances MMS resilience by reinforcing its adaptivity to the variation in production requirements. Based on a conceptual investigation of operational uncertainty and its mechanism of disruption, this study devotes to (i) formulating a performance loss-based resilience measurement with consideration of operational uncertainties and (ii) proposing a reinforcement learning-based approach to schedule MMS operation and maintenance activities for MMS components of different performance states. An industrial case study of a ferrite phase shifter manufacturing system is subsequently conducted to validate the proposed approach. Results demonstrate the effectiveness of the proposed approach in the resilience optimisation of MMSs.

Assessment of business resilience abilities: the case of industry and commerce of Santa Maria – RS

Purpose: This research aimed to evaluate the potential for resilient performance in the face of crises and adversities for companies located in the city of Santa Maria – RS (Brazil).Design/methodology/approach: We adopted a quantitative approach. The research was carried out through five sequential steps: (i) construction and validation of the research instrument; (ii) definition of the sample size and sampling procedures; (iii) data collection; (iv) data analysis and interpretation of results; and (v) elaboration of recommendations. A research instrument containing 44 questions was built and distributed among potential respondents, obtaining 87 valid answers, which corresponds to a statistically representative sample for the parameters adopted.Findings: Our sample was divided into two subsets, representing the Industrial and Commerce sectors. Resilience assessment accounted for four dimensions: the ability to respond, to anticipate, to monitor, and to learn. Results for both sectors showed scores ranging from 3.4 to 3.7 (out of 5) in the four dimensions evaluated. This reveals both sectors have been developing practices that positively contribute to the improvement of resilience, although there are opportunities for improvement.Originality/value: This research sheds light on the resilience ability of the cases surveyed, enabling managers to take action to strengthen their organizations and overcome crises and adversities. Additionally, our findings demonstrate how resilience abilities can be assessed, considering the scope of an economic sector and a geographical area. This approach can be adopted by researchers, policymakers, and development agencies to assess the resilience abilities of firms within their sphere of influence.

Revisiting Banks' Performance After the Digitalization Acceleration: The Case of Conventional Banking Industry in Indonesia

Otoritas Jasa Keuangan (OJK) facilitates digital banking acceleration by establishing regulations related to digital banking. After its implementation, banking performance in general has increased, but some banks experienced discrepancies. This study aims to analyze the comparison of banks’ fund composition, operational efficiency, and economic rentability before and during the acceleration. This research uses the comparative tests by the Wilcoxon Signed Rank Test and Paired Sample T-Test based on the existing data of nine banks listed on the Indonesia Stock Exchange (IDX) main board. The result indicates that there were significant differences in banks’ Current Account Saving Account composition, operational efficiency, and economic rentability variables. In contrast, banks’ Time Deposit composition variables did not experience significant differences before and after digitalization acceleration. This study was conducted based on the data from IDX main board banks that have provided online account opening features and experienced a decline in one of the fund composition, operational efficiency, and economic rentability performance.

A model-based approach for self-adaptive security in CPS: Application to smart grids

Security risk assessment is an important challenge in the design of Cyber Physical Systems (CPS). Even more importantly, the intrinsically dynamical nature of these systems, due to changes in their environment, as well as evolutions in their infrastructures, makes them self-adaptive systems, where security aspects have to be considered in terms of management of detections and reactions for self-protection. In this work, we propose an approach to autonomously mitigate the threats in each reconfiguration at application or infrastructure levels of CPS. We propose and implement a framework for self-adaptive security: software architecture, design method, and integration with model-based decision. We use Attack-Defense Trees for modeling threats, and our approach involves security risk assessment, taking into account its balancing and coordination with quality-of-service aspects. We formulate and formalize the on-line decision problem to be solved at each cycle of the self-adaptation control loop in terms of Constraint Programming (CP) modeling and resolution. The CP model implements a set of constraints that allow to specify secure configurations, evaluated regarding their impact on system performance to pinpoint the most relevant one portraying a good balance between the security and quality of service. We perform validation of our approach with its application to Smart Grids, more particularly to an industrial case study from RTE (the French Energy Transmission company).

Promoting the Diffusion of Sustainable Innovations through Customer Education—A Case of the Cosmetic Industry

This article investigates whether customer education about the sustainability advantage of a sustainable innovation helps promote the diffusion of such innovation using a survey and an experimental study in the cosmetic industry. Educating customers to equip them with awareness, know-how, and principal knowledge about sustainability promotes their motivation toward adoption and thus facilitates the diffusion of sustainable innovation. Specifically, results show that educating customers about cosmetic product ingredients, sustainability definition, and green certification increases the customers’ intention towards checking cosmetic products for ingredients, avoiding products that contain harmful ingredients, and purchasing a sustainable product in the next two years. Customers will also have more trust and intention to adopt certified sustainable products, and they will regard whether a product is truly sustainable as a factor more important than its price in their purchase decisions. Finally, a comprehensive list of factors that contribute to a customer’s perception and adoption of a sustainable product, as well as the ranking given by the study participants, are discussed.

ANALISIS PENYELESAIAN PERSELISIHAN PEMUTUSAN HUBUNGAN KERJA PADA PENGADILAN NEGERI JAKARTA PUSAT (PUTUSAN NOMOR 67/PDT.SUS PHI/2020/PN.JKT.PST

When handling disputes between workers and employers in industrial relations, action is required in accordance with applicable labor law. The initial step that must be taken is to carry out bipartite negotiations between the two parties to find a solution to the dispute. If bipartite negotiations are unsuccessful, the next step is to file for mediation and sue the Industrial Relations Court. The problems that arise between the Plaintiff and the Defendant relate to the mechanism for resolving disputes in termination of employment (PHK) in industrial relations, as well as whether the procedures carried out are in accordance with the statutory regulations explained in decision Number 67/Pdt.Sus-PHI/2020/ PN. JKT. PST. From this decision, it is not considered that any negotiations took place, which is the debate in this case. To answer this problem, normative juridical research was carried out with a descriptive analytical approach. This research refers to primary and secondary data which was analyzed qualitatively, and conclusions were drawn using deductive methods. The process of resolving this industrial relations case involves mediation with a mediator from the East Jakarta Social and Employment Service, as well as filing a lawsuit with the Industrial Relations Court at the local District Court. However, statutory regulations are not in accordance with the steps taken in this case, because bipartite negotiations are thought to have never occurred.

A two-stage decision model for sustainable-resilient supplier selection and order allocation under uncertain environment

PurposeThe paper aims to propose an innovative two-stage decision model to address the sustainable-resilient supplier selection and order allocation (SSOA) problem in the single-valued neutrosophic (SVN) environment.Design/methodology/approachFirst, the sustainable and resilient performances of suppliers are evaluated by the proposed integrated SVN-base-criterion method (BCM)-an acronym in Portuguese of interactive and multi-criteria decision-making (TODIM) method, with consideration of the uncertainty in the decision-making process. Then, a novel multi-objective optimization model is formulated, and the best sustainable-resilient order allocation solution is found using the U-NSGA-III algorithm and TOPSIS method. Finally, based on a real-life case in the automotive manufacturing industry, experiments are conducted to demonstrate the application of the proposed two-stage decision model.FindingsThe paper provides an effective decision tool for the SSOA process in an uncertain environment. The proposed SVN-BCM-TODIM approach can effectively handle the uncertainties from the decision-maker’s confidence degree and incomplete decision information and evaluate suppliers’ performance in different dimensions while avoiding the compensatory effect between criteria. Moreover, the proposed order allocation model proposes an original way to improve sustainable-resilient procurement values.Originality/valueThe paper provides a supplier selection process that can effectively integrate sustainability and resilience evaluation in an uncertain environment and develops a sustainable-resilient procurement optimization model.

Genesis, mechanism, and avoidance of cosmetic coating defects – An industrial case study

Film-coated tablets as solid oral dosage forms are a well-accepted way of administering drugs but are not without specific challenges during manufacturing. One relevant criterion of the final product is the visual integrity and therewith, the absence of cosmetic optical defects such as edge chipping. The aim of the present study was to examine the origin of those edge chipping defects, which were observed during commercial manufacturing of film-coated tablets, and to provide recommendations for process optimization to reduce the defect occurrence. The unraveling of the herein described phenomenon necessitated an interplay of in-depth material characterization, discrete element modeling (DEM) as well as an in-house developed optical measurement system for the automated quantification of tablet defects. As a result of this investigation, the automatic unloading step after the tablet coating process was identified as the most critical step for the occurrence of chipping defects and a replacement by manual unloading was proposed to reduce the defect propensity. The recommended optimization was subsequently confirmed in several manufacturing runs and a reduction of defect propensity by a factor of 5 was observed, highlighting the relevance and the impact of the performed thorough investigation.

Rigorous Security Analysis of RabbitMQ Broker with Concurrent Stochastic Games

Modern Internet of Things architectures encompass various computational logic and communication protocols. However, the security issues inherent in these systems pose significant risks, especially at the device edges. Addressing security threats on the deployed communication edges is imperative to ensure a robust and secure communication system. In this study, we propose an approach that utilizes the Concurrent Stochastic Game model (CSG) to specify the behavior of RabbitMQ Broker in the context of IoT systems precisely while considering potential data corruption attacks. For parametrizable evaluation, these attacks and their frequencies are learned. We implement the CSG model in PRISM games for automated analysis, leveraging reward Probabilistic Alternating Temporal Logic (rPATL) to model security requirements as game goals. Empirical validation of the work is presented via an industrial case study that shows how data corruption attacks can impact the sensed data in water dam infrastructure. This assessment gives valuable insights into the RabbitMQ deployment at the edge.

Enhancing Job Satisfaction and Productivity through Knowledge Management Infrastructure: A Case of Construction Industry

This study rigorously investigates the influence of knowledge management infrastructures (KMI) on employees’ job satisfaction (JS) within the Iranian construction sector. It specifically investigates how structural, cultural, and technological facets of KMIs affect this satisfaction. The research adopts a quantitative methodology, utilizing established measurement tools from Gold et al. for KMIs and Hackman and Oldham for JS. The empirical Information was gathered via a survey distributed to stratified random sample of 150 employees and managers from five diverse construction firms in Iran. Examining the collected data with the Partial Least Squares Structural Equation Modeling (PLS-SEM) approach, the study presents nuanced insights. It identifies that while cultural and technological infrastructures of KMIs significantly contribute to JS, the structural infrastructure does not exhibit a similar impact. Additionally, demographic factors such as age and professional experience were found to be non-contributory in the dynamics between KMIs and JS. However, gender and educational background emerged as significant moderating variables. Remarkably, employees with advanced academic qualifications reported higher satisfaction, likely due to the alignment of specialized knowledge with their professional roles. This research contributes to the current knowledge base by outlining the distinct components of KMIs that bolster JS in the construction industry, thereby offering a targeted framework for industry practitioners and policymakers to enhance employee well-being and organizational efficiency.

Using Surrogate Parameters to Enhance Monitoring of Community Wastewater Management System Performance for Sustainable Operations.

Community wastewater management systems (CWMS) are small-scale wastewater treatment systems typically in regional and rural areas with less sophisticated treatment processes and often managed by local governments or communities. Research and industrial applications have demonstrated that online UV-Vis sensors have great potential for improving wastewater monitoring and treatment processes. Existing studies on the development of surrogate parameters with models from spectral data for wastewater were largely limited to lab-based. In contrast, industrial applications of these sensors have primarily targeted large wastewater treatment plants (WWTPs), leaving a gap in research for small-scale WWTPs. This paper demonstrates the suitability of using a field-based online UV-Vis sensor combined with advanced data analytics for CWMSs as an early warning for process upset to support sustainable operations. An industry case study is provided to demonstrate the development of surrogate monitoring parameters for total suspended solids (TSSs) and chemical oxygen demand (COD) using the UV-Vis spectral data from an online UV-Vis sensor. Absorbances at a wavelength of 625 nm (UV625) and absorbances at a wavelength of 265 nm (UV265) were identified as surrogate parameters to measure TSSs and COD, respectively. This study contributes to the improvement of WWTP performance with a continuous monitoring system by developing a process monitoring framework and optimization strategy.

User journey games: automating user-centric analysis

The servitization of business is moving industry to business models driven by customer demand. Customer satisfaction is connected with financial rewards, forcing companies to invest in their users’ experience. User journeys describe how users maneuver through a service. Today, user journeys are typically modeled graphically, and lack formalization and analysis support. This paper proposes a formalization of user journeys as weighted games between the user and the service provider and a systematic data-driven method to derive these user journey games from system logs, using process mining techniques. As the derived games may contain cycles, we define an algorithm to transform user journeys games with cycles into acyclic weighted games, which can be model checked using to uncover potential challenges in a company’s interactions with its users and derive company strategies to guide users through their journeys. Finally, we propose a user journey sliding-window analysis to detect changes in the user journey over time by model checking a sequence of generated games. Our analysis pipeline has been evaluated on an industrial case study; it revealed design challenges within the studied service and could be used to derive actionable recommendations for improvement.

A Process for Monitoring the Impact of Architecture Principles on Sustainability: An Industrial Case Study

Architecture principles affect a software system holistically. Given their alignment with a business strategy, they should be incorporated within the validation process covering aspects of sustainability. However, current research discusses the influence of architecture principles on sustainability in a limited context. Our objective was to introduce a reusable process for monitoring and evaluating the impact of architecture principles on sustainability from a software architecture perspective. We sought to demonstrate the application of such a process in professional practice. A qualitative case study was conducted in the context of a Dutch airport management company. Data collection involved a case analysis and the execution of two rounds of expert interviews. We (i) identified a set of case-related key performance indicators, (ii) utilized commonly accepted measurement tools, and (iii) employed graphical representations in the form of spider charts to monitor the sustainability impacts. The real-world observations were evaluated through a concluding focus group. Our findings indicated that architecture principles were a feasible mechanism with which to address sustainability across all different architecture layers within the enterprise. The experts considered the sustainability analysis valuable in guiding the software architecture process towards sustainability. With the emphasis on principles, we facilitate industry adoption by embedding sustainability in existing mechanisms.