Industrial Case Study on Lean Manufacturing Implemented on Manufacturing Polypropylene Ropes Industry Amravati

Lean manufacturing has been one of the most standard method in the manufacturing and service industry for elimination of waste. Every manufacturing industry has to put in continuous effort for its survival in the current impulsive and competitive economy. The purpose of this paper is to investigate the adoption of lean manufacturing tools and techniques in the manufacturing industries. This paper is based on actual implementation of lean manufacturing techniques. It focuses on the execution of flow from the start until the end of the implementation, types of analysis and tools applied, evaluation methods and how the industry benefited from the implementation. In this case study we particularly focused on Shop floor management, Quality Management (QM), Supplier and Customer Management (SCM) and Workforce Management (WM). After going through various testing on implementation of Lean Manufacturing principles in Micro Small medium Enterprise (MSME), researcher studied thoughts of some author where they discussed pragmatic problems they overcome while implementing lean principles in developing economies MSME. At the end, the result shows that there is monthly increment in capital productivity and labour productivity. And decrement in inhouse rejection, breakdown hours and customer complaint from the implementation of lean.

Automated Classification of Unstructured Bilingual Software Bug Reports: An Industrial Case Study Research

Software bug report classification is a critical process to understand the nature, implications, and causes of software failures. Furthermore, classification enables a fast and appropriate reaction to software bugs. However, for large-scale projects, one must deal with a broad set of bugs from multiple types. In this context, manually classifying bugs becomes cumbersome and time-consuming. Although several studies have addressed automated bug classification using machine learning techniques, they have mainly focused on academic case studies, open-source software, and unilingual text input. This paper presents our automated bug classification approach applied and validated in an industrial case study. In contrast to earlier studies, our study is applied to a commercial software system based on unstructured bilingual bug reports written in English and Turkish. The presented approach adopts and integrates machine learning (ML), text mining, and natural language processing (NLP) techniques to support the classification of software bugs. The approach has been applied within an industrial case study. Compared to manual classification, our results show that bug classification can be automated and even performs better than manual bug classification. Our study shows that the presented approach and the corresponding tools effectively reduce the manual classification time and effort.

Collaborative Workplace Design: A Knowledge-Based Approach to Promote Human–Robot Collaboration and Multi-Objective Layout Optimization

The innovation-driven Industry 5.0 leads us to consider humanity in a prominent position as the center of the manufacturing field even more than Industry 4.0. This pushes us towards the hybridization of manufacturing plants promoting a full collaboration between humans and robots. However, there are currently very few workplaces where effective Human–Robot Collaboration takes place. Layout designing plays a key role in assuring safe and efficient Human–Robot Collaboration. The layout design, especially in the context of collaborative robotics, is a complex problem to face, since it is related to safety, ergonomics, and productivity aspects. In the current work, a Knowledge-Based Approach (KBA) is adopted to face the complexity of the layout design problem. The framework resulting from the KBA allows for developing a modeling paradigm that enables us to define a streamlined approach for the layout design. The proposed approach allows for placing resource within the workplace according to a defined optimization criterion, and also ensures compliance with various standards. This approach is applied to an industrial case study in order to prove its feasibility. A what-if analysis is performed by applying the proposed approach. Changing three control factors (i.e., minimum distance, robot speed, logistic space configuration) on three levels, in a Design of Experiments, 27 layout configurations of the same workplace are generated. Consequently, the inputs that most affect the layout design are identified by means of an Analysis of Variance (ANOVA). The results show that only one layout is eligible to be the best configuration, and only two out of three control factors are very significant for the designing of the HRC workplace layout. Hence, the proposed approach enables the designing of standard compliant and optimized HRC workplace layouts. Therefore, several alternatives of the layout for the same workplace can be easily generated and investigated in a systematic manner.

A Modular Digital Twinning Framework for Safety Assurance of Collaborative Robotics

Digital twins offer a unique opportunity to design, test, deploy, monitor, and control real-world robotic processes. In this paper we present a novel, modular digital twinning framework developed for the investigation of safety within collaborative robotic manufacturing processes. The modular architecture supports scalable representations of user-defined cyber-physical environments, and tools for safety analysis and control. This versatile research tool facilitates the creation of mixed environments of Digital Models, Digital Shadows, and Digital Twins, whilst standardising communication and physical system representation across different hardware platforms. The framework is demonstrated as applied to an industrial case-study focused on the safety assurance of a collaborative robotic manufacturing process. We describe the creation of a digital twin scenario, consisting of individual digital twins of entities in the manufacturing case study, and the application of a synthesised safety controller from our wider work. We show how the framework is able to provide adequate evidence to virtually assess safety claims made against the safety controller using a supporting validation module and testing strategy. The implementation, evidence and safety investigation is presented and discussed, raising exciting possibilities for the use of digital twins in robotic safety assurance.

Software Architecture Modeling of AUTOSAR-Based Multi-Core Mixed-Critical Electric Powertrain Controller

In this paper, we present a transition journey of automotive software architecture design from using legacy approaches and toolchains to employing new modeling capabilities in the recent releases of Matlab/Simulink (M/S). We present the seamless approach that we have employed for the software architecture modeling of a mixed-critical electric powertrain controller which runs on a multi-core hardware platform. With our approach, we can achieve bidirectional traceability along with a powerful authoring process, implement a detailed model-based software architecture design of AUTOSAR system including a detailed data dictionary, and carry out umpteen number of proof-of-concept studies, what-if scenario simulations and performance tuning of safety software. In this context, we discuss an industrial case study employing valuable lessons learned, our experience reports providing novel insights and best practices followed.

An industrial case study: QbD to accelerate time-to-market of a drug product

The use of a Quality by Design (QbD) approach in the development of pharmaceutical products is known to bring many advantages to the table, such as increased product and process knowledge, robust manufacturing processes, and regulatory flexibility regarding changes during the commercial phase. However, many companies still adhere to a more traditional pharmaceutical process development—in some cases due to the difficulty of going from a theoretical view of QbD to its actual application. This article presents a real-world case study for the development of an industrial pharmaceutical drug product (oral solid dosage form) using the QbD methodology, demonstrating the activities involved and the gains in obtaining systematic process and product knowledge.

Reliability of quantitative risk analysis through an industrial case study

PurposeThe purpose of this paper is to analyze the reliability of the quantitative risk model used for planning inspection and maintenance activities. The objective is to critically discuss the factors that contribute to the probability and consequence of failure calculations.Design/methodology/approachThe case study conducted using one of the most widely deployed risk models in the oil and gas industry where a full assessment was performed on an offshore gas producing platform.FindingsThe generic failure frequencies used as the basis for calculating the probability of failure are set at a value representative of the refining and petrochemical industry's failure data. This failure database does not cover offshore. The critical discussion indicated the lack of basis of the coefficient of variances, prior probabilities and conditional probabilities. Moreover, the risk model does not address the distribution of thickness measurements, corrosion rates and inspection effectiveness, whereas only overall deterministic values are used; this requires judgment to determine these values. Probabilities of ignition, probabilities of delayed ignition and other probabilities in Level 1 event tree are found selected based on expert judgment for each of the reference fluids and release types (i.e. continuous or instantaneous). These probabilities are constant and independent of the release rate or mass and lack of constructed model. Defining the release type is critical in the consequence of the failure methodology, whereas the calculated consequences differ greatly depending on the type of release, i.e. continuous or instantaneous. The assessment results show that both criteria of defining the type of release, i.e. continuous or instantaneous, do not affect the calculations of flammable consequences when the auto-ignition likely is zero at the storage temperature. While, the difference in the resulted toxic consequence was more than 31 times between the two criteria of defining the type of release.Research limitations/implicationsThere is a need to revamp this quantitative risk model to minimize the subjectivity in the risk calculation and to address the unique design features of offshore platforms.Originality/valueThis case study critically discuss the risk model being widely applied in the O&G industry and demonstrates to the end-users the subjectivity in the risk results. Hence, be vigilant when establishing the risk tolerance/target for the purpose of inspection and maintenance planning.

Improving the Requirements Engineering Process Through Automated Support: An Industrial Case Study

Although Distributed Software Development (DSD) has been a growing trend in the software industry, performing requirements management in such conditions implies overcoming new limitations resulting from geographic separation. SIDIA is a Research and Development (R&D) Institute, located in Brazil, responsible for producing improvements on the Android Platform for Samsung Products in all Latin America. As we work in collaboration stakeholders provided by Mobile Network Operators (MNO) from Latin countries, it is common that software requirements be provided by external stakeholders. As such, it is difficult to manage these requirements due to the coordination of many different stakeholders in a distributed setting. In order to minimize the risks, we developed a tool to assist our requirements management and development process. This experience paper explores the experience in designing and deploying a software approach that facilitates (I) Distributed Software Development, (II) minimizes requirements error rate, (III) teams and task allocations and (IV) requirements managements. We also report three lessons learned from adopting automated support in the DDS environment.