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In the context of predictive quality in production, there is a need to explain and understand the predictive models used, as well as the dependencies present in the underlying data. For this purpose, we develop a framework for model-independent interpretation of predictive models to enable data-driven, process- and product-oriented decisions. This framework combines different model-agnostic interpretation methods and structures them into two modules, one for a process-oriented view and the other for a product-oriented view. In addition, an implementation concept for the two modules in a machine learning pipeline is also provided. [ABSTRACT FROM AUTHOR]

Despite complexity management efforts in product development, manufacturing worldwide is challenged by high and increasing complexity. Measuring complexity in production is crucial for its management, for that a practicable measurement tool covering complexity drivers and resulting complexity effects is proposed in this paper. The outcome of a pilot study conducted in four production plants of different companies is presented. The findings confirm strong correlations between drivers and negative effects of complexity, indicating that the complexity measures presented are good predictors for the impact of inadequate complexity. Furthermore, the tool allows identifying relevant complexity drivers. [ABSTRACT FROM AUTHOR]

In the era of cyber-physical environments, indoor asset tracking systems enable to monitor and control production in a smarter way than ever before, as they are capable of providing data about the location of various equipment on the shop-floor in near real time. The right use of this data contributes to the improvement of production control and management processes, however, utilization of the related information often requires novel methods. In the paper, decision-making approaches are presented that rely on advanced data analytics for asset location systems. The efficiency of the results are presented through an industry related use-case. [ABSTRACT FROM AUTHOR]

In the era of the industrial digitalization, the availability of shop-floor data is not a question anymore, but rather the exploitation of the underlying information. With advanced sensor technologies, detailed data can be obtained about products, resources and processes in near real time, however, still there are gaps between the collection of the data, and the utilization of it. The greatest current challenge is the use of available data in decisionmaking processes that brings the real business value for companies, to keep their competitiveness and internal efficiency. In the paper, a reference model of an industrial data analytics platform is presented that supports the integration of various analytics solutions with enterprise level decision support tools, such as planning and scheduling systems. The reference model is composed of various layers, supporting the collection, storage and analysis of data coming from various sources. In addition to its business intelligence related dashboarding and visualization functions, it provides the opportunity of linking the analytics results with other software applications. In order to highlight the capabilities of the proposed model, possible application domains and use-cases are presented, reflecting real industrial needs. [ABSTRACT FROM AUTHOR]

Applying lean can boost a firm’s performance significantly by focusing on value-adding activities. Additionally, Industry 4.0 is regarded as another promising trend in industry. Combining these developments resulted in terms like "lean 4.0". However, the existing literature lacks a comprehensive and detailed conjunction of both paradigms. This paper builds upon this research gap with a twofold aim: Firstly, the target is to build upon existing groundwork to conclude whether lean management and Industry 4.0 can complement each other. Secondly, this work considers how Industry 4.0 can support specific lean methods. This is exemplified by an electric drives production use case. [ABSTRACT FROM AUTHOR]

For years, companies have tried to figure out how to consistently organize their businesses for improving quality and efficiency, and at the same time reduce costs and lead times. Lean principles and techniques have become a benchmark for Western manufacturing companies, founded on the success of the Toyota Production System. Despite its popularity, many companies still struggle to achieve a successful and lasting lean implementation. Existing research indicate that both organizational and technical barriers are important, such as lack of management support and commitment, poor involvement of employees, and excessive confidence in lean tools and practices. A gap in current research is the limited focus on identifying how different groups at different hierarchical levels in an organization perceive barriers to lean implementation. Unless the opinions of different groups are taken into account, efforts to overcome the barriers may be misguided. This paper reports on a two-year in-depth single case study of barriers to lean implementation, aiming at understanding why the company only to a certain extent has succeeded with their lean activities. Based on 28 interviews and observations, results indicate that the different groups at different hierarchical levels experience different types of barriers. The article will provide an important contribution to how companies can organize lean implementation processes better for future success, which should be relevant to both academia and industry. [ABSTRACT FROM AUTHOR]

Engineering students are often lectured and afterwards examined in a knowledge-oriented way. The question is if the students we identify with those methods as good students are also better problem solvers in practice. To review if there is any correlation between knowledge and the development of competencies, students need to a) perform a written examination and b) solve real industrial tasks at the Process Learning Factory CiP like rebalancing a production line. Regarding a), students gain the theoretical knowledge in a classroom lecture to the topic „Lean Production” and write an exam. Regarding b), videos recorded showing the actions tasks are evaluated regarding the presence of problem solving competencies. A comparison of the test results and the action tasks evaluation clarifies whether the existence of knowledge leads to a similar strong development of competencies. The evaluation of the learning success shows that the student groups achieve a good and very good competency development in the lecture modules “line balancing”, “kanban” and “systematic problem solving”. The respective lecture module is confirmed by a high degree of students’ success. However, a correlation between the level of knowledge and competency cannot be clearly established because on the one hand students with good exam results achieve a good and very good degree of competency development. On the other hand students with a bad exam result achieve nevertheless a comparatively good competency development degree. Nevertheless, as a trend it can be confirmed that consolidated knowledge is one important prerequisite for the ability to act in practice. [ABSTRACT FROM AUTHOR]

Modern Cooperative Engineering approaches suggest a transparent tracking of production costs during development stages. The traditional concept of Engineered Hours per Product, originally developed for the automotive industry, focusses on specific production and assembly times. Necessary but auxiliary tasks are ignored since their reduction is within the domain of production departments. Thereby this approach promotes the decrease of production time but does not give an adequate measure to compare design alternatives. This paper presents a complementary approach based on the assumption that the production system has reached a stable status and remains relatively constant for new variants. Based on existing products core time drivers based on features are successively identified until an adequate approximation of the time for the current product is achieved. Those time drivers thereby include the total time to perform the task, including auxiliary task and can be used during the development stage. The paper concludes with an industrial case study to illustrate the benefits. [ABSTRACT FROM AUTHOR]

Continuous improvement [CI], as culture, tools and methods, is critical to manufacturing companies’ competitive position. Research has documented that as many as two out of three CI programs fail, in the sense of not meeting goals and expectations. While poorly designed CI systems and misguided use of tools and methods may explain some failed CI initiatives, surveys and expert polls indicate that the main barriers to CI success are organizational and managerial. This paper reports on a case study of barriers to CI. The case company, a medium-sized manufacturer of maritime systems, has achieved only partial success with CI, despite repeated efforts. Unsurprisingly, both technical and organizational barriers are important, but the relative importance attributed to the different barriers is strikingly dissimilar across hierarchical levels in the organization. While top managers attribute the limited success to shortcomings of information systems and improvement methods, workers primarily point to limited support and commitment from management, in addition to other organizational factors such as lack of involvement, motivation and teamwork. Middle managers acknowledge both groups of barriers, but tend to agree more with the workers’ view. If these findings are generalizable beyond the single case-company, there are important implications for both research and practice. Research should appreciate the complex attribution of barriers, by complementing conventional surveys with in-depth qualitative analysis. Practically, unless the opinions of different occupation groups at different hierarchical levels are listened to, efforts to overcome the barriers may be misguided. In addition, top managers should learn to take the roles of CI champions, who not only allocate resources to CI, but also actively encourage, follow-up and reward the appropriate use of CI tools and methods. [ABSTRACT FROM AUTHOR]

Determining lot sizes in production areas is an essential task of production planning and control. Due to the growing number of product variants, calculating economical lot sizes is becoming increasingly important in the industrial practice. Although planning lot sizes plays an important role in industrial production, existing methods only partially consider the variety of impacts. This paper presents existing methods and discusses their impact on the multi-criteria objective achievement of industrial companies. Based on actual case studies the logistical and economical relevance of determining lot sizes is illustrated and the suitability of different approaches for industrial practice is discussed. [ABSTRACT FROM AUTHOR]

Abstract: The ideas of Group Technology and Cellular Manufacturing have been a research topic for decades. Although widely implemented in assembly, the principles of flow production as central element of Lean Production have not often been transferred successfully to machining areas yet. In times of continuously rising hardware complexity Cellular Manufacturing is an alternative approach to enable both, flow production and volume flexibility in machining, but can rarely be found in Europe. Current research activities focus on identifying relevant performance indicators to evaluate economic fields of application of Cellular Manufacturing using the example of milling. [Copyright &y& Elsevier]

Abstract: Fiber-reinforced plastics are a lightweight material with outstanding mechanical properties. On the one hand the application of those materials can have an outstanding contribution to product performance (e.g. energy efficiency). On the other hand fiber- reinforced plastics are not used very frequently due to their high manufacturing costs. At the same time, industrial production faces megatrends within a turbulent environment asking for highly individualized products and very short and reliable delivery times. Motivated by the combination of those two aspects, we propose an enhanced production control method for the manufacturing of preimpregnated fiber (prepreg) parts based on a survey among manufacturers of such parts. [Copyright &y& Elsevier]