@inproceedings{580, abstract = {{Additive Manufacturing (AM) is increasingly used to design new products. This is possible due to the further development of the AM-processes and materials. The lack of quality assurance of AM built parts is a key technological barrier that prevents manufacturers from adopting. The quality of an additive manufactured part is influenced by more than 50 parameters, which make process control difficult. Current research deals with using real time monitoring of the melt pool as feedback control for laser power. This paper illustrates challenges and opportunities of applying statistical predictive modeling and unsupervised learning to control additive manufacturing. In particular, an approach how to build a feedforward controller will be discussed.}}, author = {{Scheideler, Eva and Ahlemeyer-Stubbe, Andrea}}, booktitle = {{ Production engineering and management : proceedings 7th international conference, September 28 and 29, 2017, Pordenone, Italy }}, editor = {{Padoano, Elio and Villmer, Franz-Josef}}, isbn = {{978-3-946856-01-6}}, keywords = {{Additive manufacturing, Process control, Predictive modeling, Predictive control}}, location = {{Pordenone, Italy}}, number = {{1}}, pages = {{3--12}}, title = {{{Quality Control of Additive Manufacturing Using Statistical Prediction Models}}}, volume = {{2017}}, year = {{2017}}, } @inproceedings{581, author = {{Scheideler, Eva and Villmer, Franz-Josef}}, booktitle = {{Rapid.Tech – International Trade Show & Conference for Additive Manufacturing}}, isbn = {{978-3-44645459-0}}, number = {{1}}, pages = {{10--24}}, publisher = {{Carl Hanser Verlag GmbH & Co. KG}}, title = {{{Anforderungen an integrierte Prozessketten in der Additiven Fertigung}}}, doi = {{10.3139/9783446454606.001}}, year = {{2017}}, } @article{609, abstract = {{Einfach, ohne Expertenwissen anzuwenden – solch ein Planungswerkzeug spart Zeit und Geld. Dieser Artikel stellt eine neue, effiziente Berechnungsmöglichkeit vor, die z.B. Vertriebsmitarbeiter oder Architekten befähigt, Risiken bezüglich Durch‐ oder Absturzsicherheit bei allseitig gelagerten Verglasungen früh in der Planung schnell abzuprüfen. Dabei werden statistische Modelle und Simulationsberechnungen eingesetzt. Verifiziert wurde die Methode gemäß DIN 18008 Teil 4 und Teil 6 mit den Möglichkeiten der Finite‐Element‐Rechnung und Referenzdatensätzen. Sie kann eine finale statische Beurteilung (z.B. prüffähige Statik) nicht ersetzen, doch sie kann im Lauf der Planung verlässliche Abschätzungen liefern und somit Geld und Zeit einsparen.}}, author = {{Scheideler, Eva and Ahlemeyer-Stubbe, Andrea and Scheideler, Josef}}, issn = {{2509-7075}}, journal = {{ce/papers : Proceedings in Civil Engineering}}, number = {{1}}, pages = {{142--152}}, publisher = {{Ernst & Sohn, a Wiley brand }}, title = {{{Statistische Modellierung zur Unterstützung von Industrie 4.0 im Glasbau}}}, doi = {{10.1002/cepa.16}}, volume = {{1}}, year = {{2017}}, } @inproceedings{610, author = {{Deuter, Andreas and Otte, Andreas and Höllisch, Daniel}}, booktitle = {{Wissenschaftsforum Intelligente Technische Systeme (WInTeSys) 2017}}, editor = {{Trächtler, Ansgar}}, location = {{Paderborn}}, pages = {{211--222}}, title = {{{Methodisches Vorgehen zur Entwicklung und Evaluierung von Anwendungsfällen für die PLM/ALM-Integration}}}, volume = {{369}}, year = {{2017}}, } @proceedings{309, abstract = {{It is our pleasure to introduce the seventh edition of the International Conference on Production Engineering and Management (PEM), an event that is the result of the joint effort of the University of Trieste and the Ostwestfalen- Lippe University of Applied Sciences. The conference has been established as an annual meeting under the Double Degree Master Program “Production Engineering and Management” by the two partner universities. This year the conference is hosted at the university campus in Pordenone. The main goal of the conference is to offer students, researchers and professionals in Germany, Italy and abroad, an opportunity to meet and exchange information, discuss experience, specific practices and technical solutions for planning, design and management of manufacturing and service systems and processes. As always, the conference is a platform aimed at presenting research projects, introducing young academics to the tradition of symposiums and promoting the exchange of ideas between the industry and the academy. This year’s special focus is on industry sustainability, which is currently a major topic of discussion among experts and professionals. Sustainability can be considered as a requirement for any modern production processes and systems, and also has to be embedded in the context of Industry 4.0. In fact, the features and problems of industry 4.0 have been widely discussed in the last editions of the PEM conference, in which efficiency and waste reduction emerged as key factors. The study and development of the connections between future industry and sustainability is therefore critical, as highlighted in the recent “German Sustainable Development Strategy and the 2030 Agenda”. Accordingly, the seventh edition of the PEM conference aims to offer a contribution to the debate. The conference program includes 25 speeches organized in six sessions. Three are specifically dedicated to “Direct Digital Manufacturing in the context of Industry 4.0” and “Technology and Business for Circular Economy and Sustainable Production”. The other sessions are covering areas of great interest and importance to the participants of the conference, which are related to the main focus: “Innovative Management Techniques and Methodologies”, “Industrial Engineering and Lean Management” and “Wood Processing Technologies and Furniture Production”. The proceedings of the conference include the articles submitted and accepted after a careful double-blind refereeing process.}}, editor = {{Padoano, Elio and Villmer, Franz-Josef}}, isbn = {{978-3-946856-01-6}}, location = {{Pardenone, Italy}}, number = {{.}}, pages = {{248}}, title = {{{Production Engineering and Management}}}, year = {{2017}}, } @inproceedings{457, abstract = {{Additive Manufacturing (AM) increasingly enables the realization of structures, which have a much greater freedom of design und can therefore better use nature as a design ideal. Bionic design principles have already been introduced into general design approaches, and several topology optimization systems (TO) are available today to increase structural stiffness and to enable lightweight design. AM and TO, used in synergy, promise completely new application areas. However, staircase effects resulting from a layer-by-layer build process and unavoidable support structures which must be mechanically removed afterwards are disadvantageous with respect to surface texture and strength properties. The present article addresses the question of how far the notches resulting from the staircase effect of Additive Manufacturing and the support structures removed decrease the strength of components. Most engineers try to follow the inner flow of forces in a part’s design by smoothening surfaces in notched areas. Considering this, a elected component is investigated with finite element analysis (FEA) with special regard for the concentration of tress arising from surface notch effects. An outlook is given as regards how a reduction of the notch effect from the taircase effect can be achieved effectively.}}, author = {{Scheideler, Eva and Villmer, Franz-Josef and Adam, G. and Timmer, Mirco}}, booktitle = {{Production Engineering and Management Proceedings 6th International Conference}}, editor = {{Villmer, Franz-Josef and Padoano, Elio}}, isbn = {{978-3-946856-00-9}}, keywords = {{Additive Manufacturing, Topology optimization, Staircase effect, Support structures, Stress concentration, Lightweight construction, Design rules, Notch effect}}, location = {{Lemgo}}, number = {{1}}, pages = {{39--50}}, title = {{{Topology Optimization and Additive Manufacturing – A Perfect Symbiosis?}}}, year = {{2016}}, } @misc{7790, author = {{Deuter, Andreas and Rizzo, Stefano}}, booktitle = {{Procedia Technology}}, issn = {{2212-0173}}, keywords = {{PLM, ALM, OSLC}}, pages = {{405--412}}, publisher = {{ Elsevier}}, title = {{{A Critical View on PLM/ALM Convergence in Practice and Research}}}, doi = {{10.1016/j.protcy.2016.08.052}}, volume = {{26}}, year = {{2016}}, } @inproceedings{584, abstract = {{Due to the continuing trend towards more complexity of products with an increasing number of variants and smaller lot sizes, the assembly often takes place -despite relatively high labor costs in Western industrialized nations -manually or partially automated. An outsourcing or relocation of assembly function abroad is not suitable in most cases.Therefore, it is increasingly important to reduce process variations and waste in manual assembly processes. Assistance systems have the potential, depending on the situation, to assist the worker in his work, to reduce error rate and to increase productivity. In a first part of the paper an overview will be given to different types of assembly assistance systems. Then a morphological chart is developed, which can provide assistance in selecting or comparing assembly assistance systems. With the help of this chart an assembly assistant system is presented. Finally a quick look is taken at further research being done in this area.}}, author = {{Hinrichsen, Sven and Riediger, Daniel and Unrau, Alexander}}, booktitle = {{Production Engineering and Management}}, editor = {{Villmer, Franz-Josef and Padoano, Elio}}, isbn = {{978-3-946856-00-9}}, keywords = {{Assistance systems, Manual assembly, Morphology}}, location = {{Lemgo}}, number = {{01}}, pages = {{3--14}}, title = {{{Assistance Systems in Manual Assembly}}}, year = {{2016}}, } @inproceedings{586, abstract = {{Under the circumstance of advanced globalization, it is increasingly difficult for production companies to remain competitiveness. Many of them are forced to restrict budget and reduce production costs. In addition, the customization of product increases continuously. This results in extension of product variation and reduction of product life cycle. Therefore, the companies need a high flexibility to respond quickly to changes in the market and to customer requirements. Lean thinking, as a powerful tool, has been implemented by many companies in production and manufacturing. In order to avoid waste in lean manufacturing, it is necessary to manage efficiently the material flow. In this study, for a lean material handling system in the lean manufacturing of a company, an in-plant milk-run distribution system is taken into consideration. The system consistsof vehicles, which move periodically in certain routes. The materials are delivered in short intervals from a central storage area to several points of use in the production. By using milk-run in plant, the material handling processes can be standardized and therefore the waste can be eliminated. One additional aim of the study with milk-run distribution for the material provision is to minimize the handling time, which determines directly the personal costs. In order to realize the aim, the work has beendivided into several steps. At first, the production processes, especially the material provision for the production have been analyzed. Secondly, the technological solutions have been analyzed in order to handle different loading units required by different machines in the production. Thirdly, the milk-run distribution for lean production is formulated as an optimization problem with the object of minimizing the number of vehicles and the distance traveled under the constraints of specific time periods, capacity of vehicle and related stations etc. Fourthly, two optimization methods are developed in order to find the optimal solution for the milk-run problem and the performance of different methods is also compared.}}, author = {{Li, Li and Schulze, L.}}, editor = {{Villmer, Franz-Josef and Padoano, Elio}}, isbn = {{978-3-946856-00-9}}, keywords = {{Milk-Run, Material provision, Lean production, Genetic algorithm}}, location = {{Lemgo}}, number = {{1}}, pages = {{65--76}}, title = {{{In-Plant Milk-Run Distribution for Material Provision Optimization in Lean Production}}}, year = {{2016}}, } @inproceedings{587, abstract = {{Development engineers are most valued for their excellence in physical product development, but on the flipside, project managers face problems when trying to fit them into effectively running development processes. Because of the advantages of Lean Management in production (Lean Production), process managers often try to transfer lean principles directly to development processes, not considering that major differences exist between well-described production processes and new product development processes which include much more uncertainty and risk. Nevertheless, several lean principals are applicable in product development. This paper describes five lean development insights (LDIs) which were found when optimizing an entire product realization process. Lean principles have been examined and then translated to collaboration between product development and tool manufacturing at a globally operating German family-run company. These LDIs are meant to help project and process managers, consultants and developers to rethink their ways of organizing product development. The application of these insights will result in increased transparency, intensified collaboration, improved processes and quality, shortened lead times, and also eliminate waste.}}, author = {{Riediger, M. and Villmer, Franz-Josef}}, booktitle = {{Production Engineering and Management}}, editor = {{Villmer, Franz-Josef and Padoano, Elio}}, isbn = {{978-3-946856-00-9}}, keywords = {{Lean development, Collaboration, Agile, PLM, Frontloading, Simultaneous engineering}}, location = {{Lemgo}}, number = {{1}}, pages = {{111--122}}, title = {{{Five Insights in Effectively Managing Product Development}}}, year = {{2016}}, } @inproceedings{590, abstract = {{Against the background of rising overhead costs in manufacturing companies the application of methods of overhead cost management is of increasing importance. Within this article existing approaches of cost management are explained in principle. Based on these approaches a new complementary approach of managing costs with the help of costs elasticity ratios is described by a case study. The method is based on the hypothesis that there are no fixed personnel costs, but personnel costs with different elasticity with respect to the volume of orders. Personnel costs elasticity (ε) is derived from the quotient of the relative change in personnel costs (k) and the relative change of the order volume (q) of a billing month (i). The method aims to increase the flexibility of overhead costs, but can also be applied with respect to so-called direct costs. In this case, the question arises as to what extent the direct costs actually develop proportional elastic over time.}}, author = {{Hinrichsen, Sven}}, booktitle = {{Production Engineering and Management}}, editor = {{Villmer, Franz-Josef and Padoano, Elio}}, isbn = {{978-3-946856-00-9}}, keywords = {{Cost management, Overhead costs, Direct costs, Labor costs, Elasticity}}, location = {{Lemgo}}, number = {{1}}, pages = {{123--131}}, title = {{{How Elasticity Indicators Support Cost Management}}}, year = {{2016}}, } @inproceedings{593, abstract = {{Due to the increased individualization of customer demands in the last 20 years, the production systems are required to be more flexible and scalable. It is the samefor the material flow system with automated guided vehicles (AGVs). To realize the flexibility and scalability, it is recommended to decentralized control the vehicles. As an attempt, a concept of swarm intelligence with Radio Frequency Identification (RFID) is proposed and introduced in this article. The concept is supposed to be used for automated guided vehicle systems in which objects have to be transported from place to place. Therefore the object has to be self-organized and has to manage its own transport. In this context the vehicles have to choose the most optimal transportation. Swarm intelligence is a topic which deserves a high level of attention as a method to realize high flexibility and scalability.}}, author = {{Cantauw, Alisa Maria and Li, Li}}, booktitle = {{Department of Production Engineering and Management}}, editor = {{Villmer, Franz-Josef and Padoano, Elio}}, isbn = {{978-3-946856-00-9}}, keywords = {{Swarm intelligence, Automated guided vehicle system, RFID, Internet of things, Multi-agent system}}, location = {{Lemgo}}, number = {{1}}, pages = {{133--143}}, title = {{{Application of Swarm Intelligence for Automated Guided Vehicle Systems}}}, year = {{2016}}, } @inproceedings{594, abstract = {{Due to steadily increased demand for customized products, as well as their enhanced complexity and shorter product lifecycles, companies in all industries require a reliable prediction of the expected product development costs from the very start of product realization. Incorrectly estimated project costs may lead to serious consequences in the course of a development project. For example, offers are most often based on such early cost estimations and consequently, a major safety margin has to be added, which may result in the refusal of an order. A too low estimation of the costs of aproduct development project, on the other hand, may result in a loss for the project.In this paper, a software tool is presented for the prediction of product development costs which offers the user the ability to create a more accurate prediction of project costs on the basis of a minimum of retrograde project information. By combining a parametric cost model and cost result with stochastic character, based on the Monte Carlo method, in one software system, it is possible to significantly improve projectcost estimations.}}, author = {{Otte, Andreas and Scheideler, Eva and Villmer, Franz-Josef}}, booktitle = {{Department of Production Engineering and Management}}, editor = {{Villmer, Franz-Josef and Padoano, Elio}}, isbn = {{978-3-946856-00-9}}, keywords = {{Cost prediction, Product realization projects, Monte Carlo method, Parametric cost model, Software tool}}, location = {{Lemgo}}, number = {{1}}, pages = {{281--292}}, title = {{{Project Cost Estimator - A Parameter-Based Tool to Predict Product Realization Costs at a Very Early Stage}}}, year = {{2016}}, } @inproceedings{472, abstract = {{In the context of Industrie 4.0 respectively direct digital manufacturing, seamless process chains are an important factor. The objective is to shorten the time between quoting for individually designed products and their production and delivery. Therefore, reliable automated and fast evaluation procedures are needed to ensure the quality of the individually designed products in terms of product safety and reliability. This paper aims to demonstrate how a metamodel, generated on simulated data, adapts to the type of product and delivers the required quality and evaluation procedure. The metamodel guarantees the requested characteristics of the final product without the consultation of human expert knowledge. As proof of concept, a simple, well-documented task from the field of construction has been chosen. The estimation from of the metamodel will meet all safety requirements, is based on the individual input variables and is confirmed without expert interaction. Fast, reliable prediction models deriving from complex simulation models are indispensable conditions for direct digital manufacturing. Using metamodels in automation contexts will be a foundation of manufacturing in future.}}, author = {{Scheideler, Eva and Ahlemeyer-Stubbe, Andrea}}, booktitle = {{Production engineering and management : proceedings 6th international conference, September 29 and 30, 2016 Lemgo, Germany }}, editor = {{Villmer, Franz-Josef and Padoano, Elio}}, keywords = {{Simulation, Metamodel, Computer experiment, Design of experiments}}, location = {{Lemgo}}, number = {{1}}, pages = {{269--280}}, publisher = {{Hochschule Ostwestfalen-Lippe}}, title = {{{Expert Knowledge Systems to Ensure Quality and Reliability in Direct Digital Manufacturing Enviroments}}}, volume = {{2016}}, year = {{2016}}, } @inproceedings{473, abstract = {{Additive Manufacturing (AM) describes a number of technologies that generate three-dimensional objects directly from CAD data by joining volume elements. Dental technology is one sector in which the benefits of AM come into effect, as parts such as frameworks or implants are unique objects often with freeform shapes. These objects are difficult and expensive to produce with subtractive or formative technology. During the last decades, the application of digital technologies in the dental industry has increased. Therefore AM has also evolved to become a standard dental framework manufacturing process. While previously the dental laboratory did the complete manufacturing of dental frameworks, AM parts are usually produced by service providers, thus increasing the number of process participants. Under these circumstances, a reliable high quality production must be ensured. This requires a comprehensive Quality Management (QM) concept for the whole process chain. A first step in the evelopment of this QM concept is the definition of the product requirements, from which process specifications can be determined. These specifications build the basis for evaluating the process capability of the Additive Manufacturing process.}}, author = {{Huxol, Andrea and Villmer, Franz-Josef}}, booktitle = {{Production Engineering and Management}}, editor = {{Villmer, Franz-Josef and Padoano, Elio}}, keywords = {{Additive Manufacturing, Dental frameworks, Quality management, Digital manufacturing}}, location = {{Lemgo}}, number = {{1}}, pages = {{15--26}}, title = {{{Special Requirements for Additive Manufacturing of Dental Frameworks}}}, year = {{2016}}, } @proceedings{333, abstract = {{The annual International Conference on Production Engineering and Management takes place for the sixth time his year, and can therefore be considered a well - established event that is the result of the joint effort of the OWL University of Applied Sciences and the University of Trieste. The conference has been established as an annual meeting under the Double Degree Master Program ‘Production Engineering and Management’ by the two partner universities. The main goal of the conference is to provide an opportunity for students, researchers and professionals from Germany, Italy and abroad, to meet and exchange information, discuss experiences, specific practices and technical solutions used in planning, design and management of production and service systems. In addition, the conference is a platform aimed at presenting research projects, introducing young academics to the tradition of Symposiums and promoting the exchange of ideas between the industry and the academy. Especially the contributions of successful graduates of the Double Degree Master Program ‘Production Engineering and Management’ and those of other postgraduate researchers from several European countries have been enforced. This year’s special focus is on Direct Digital Manufacturing in the context of Industry 4.0, a topic of great interest for the global industry. The concept is spreading, but the actual solutions must be presented in order to highlight the practical benefits to industry and customers. Indeed, as Henning Banthien, Secretary General of the German ‘Plattform Industrie 4.0’ project office, has recently remarked, “Industry 4.0 requires a close alliance amongst the private sector, academia, politics and trade unions” in order to be “translated into practice and be implemented now”. PEM 2016 takes place between September 29 and 30, 2016 at the OWL University of Applied Sciences in Lemgo. The program is defined by the Organizing and Scientific Committees and clustered into scientific sessions covering topics of main interest and importance to the participants of the conference. The scientific sessions deal with technical and engineering issues, as well as management topics, and include contributions by researchers from academia and industry. The extended abstracts and full papers of the contributions underwent a double - blind review process. The 24 accepted presentations are assigned, according to their subject, to one of the following sessions: ‘Direct Digital Manufacturing in the Context of Industry 4.0’, ‘Industrial Engineering and Lean Management’, ‘Management Techniques and Methodologies’, ‘Wood Processing Technologies and Furniture Production’ and ‘Innovation Techniques and Methodologies.}}, editor = {{Villmer, Franz-Josef and Padoano, Elio}}, isbn = {{978-3-946856-00-9}}, location = {{Lemgo}}, number = {{1}}, pages = {{304}}, title = {{{Production Engineering and Management}}}, year = {{2016}}, } @inproceedings{432, abstract = {{The trend of increasing technological complexity of machines mainly correlates with the integration of additional functions in machines. Increasing functionality of the machines leads to an increased number of control elements, which limits the clarity of the machine operation and leads to higher cognitive demands in the machine operation. Due to the growing functional range of production machines the demand of usability for the operating systems continues to grow. The selection and design of icons for the identification of controls contributes significantly to usability, especially for intuitive operation of production machines. The aim of this study is to investigate the intuitive usability of production machines, to consider its use of graphical elements (icons) and to derive recommendations for a demand-oriented selection and design of icons. To achieve this goal, laboratory studies at five modern production machines (laser sintering machine, CNC universal lathe, plastic injection molding machine, laser processing machine, woodworking machine) - each with different operating concept - were performed. The results of the study show that the used symbols in the examined machines are only limited self-explanatory and intuitive, and thus have significant deficits for easy and intuitive operation. Especially the combination of screens and electronic keys or switches was often criticized and leads to uncertainty in the operation. As a result, recommendations for the design of icons on production machines are given. }}, author = {{Riediger, Daniel and Hinrichsen, Sven and Schlee, Alexander}}, booktitle = {{Production Engineering and Management}}, editor = {{Villmer, Franz-Josef and Padoano, Elio}}, isbn = {{978-3-941645-11-0}}, keywords = {{Usability, production mach ine, icons, usability, hum an-machine compatibility}}, location = {{Trieste}}, number = {{1}}, pages = {{123--130}}, publisher = {{Hochschule Ostwestfalen-Lippe}}, title = {{{Ergonomic Design of Graphical Control Elements on Production Machines}}}, year = {{2015}}, } @inproceedings{585, abstract = {{Many low-cost 3D printers have been brought to market over the last couple of years. Most of them apply a Fused Layer Manufacturing (FLM) process, and have made 3D printing a great success amongst hobbyists, the maker community and students. One drawback of such inexpensive equipment is a limited build envelope, which prevents this from becoming a significant contributor to industrial production. To overcome these limits, it is not sufficient to simply upscale dimensions, but the overall concept of such machines must be completely re-thought, as well as the concepts behind several building blocks, components and the process software system. Problems such as shrinkage of build material, support material and machine parts in combination with long printer head travels, temperature distribution and moisture effects all have to be solved. In addition, larger parts need longer process times. Therefore, reduction of process times and an increase in productivity are necessary in order to enable economic production. Some of these problems can be solved by using more than one printer head for production, by using new materials and inventing new nozzle systems as distinct solutions for big printers. Nevertheless, to solve all these problems, the development of special machines for large parts is necessary: not component-wise but as a whole system. Large parts could then be successfully produced in several industries, using large, inexpensive FLMmachines. }}, author = {{Villmer, Franz-Josef and Witte, Lars}}, booktitle = {{Production Engineering and Management}}, editor = {{Padoano, Elio and Villmer, Franz-Josef}}, isbn = {{978-3-941645-11-0}}, keywords = {{3D printing, FLM, build envelope, large-scale, thermoplastic polymers}}, location = {{Trieste, Italy}}, number = {{1}}, pages = {{111--122}}, title = {{{Large Scale 3D-Printers: The Challenge of Outgrowing Do-It-Yourself}}}, year = {{2015}}, } @inproceedings{588, abstract = {{While common measurement techniques like gloss or color measurement are widely used in industry for quality assessment of furniture high gloss surfaces, they indicate only a weak correlation to the quality perceived by the customer. Topography based approaches achieve higher correlation to human perception but are often based on linear measurement which cannot be applied for an overall assessment of larger surfaces. Thus an algorithm was developed to calculate a specific value based on topographic features, such as orange peel, within the research project ‘Development of a comprehensive quality concept for furniture high gloss surfaces’, funded by the federal Ministry of Education and Research. For the evaluation of short waved structures on furniture high gloss surfaces the ratio of hill height to hill area was chosen. This parameter proves to be applicable for an evaluation of the extent of a single. }}, author = {{Huxol, Andrea and Riegel, Adrian and Dekomien, Kerstin}}, booktitle = {{Production Engineering and Management}}, editor = {{Padoano, Elio and Villmer, Franz-Josef}}, isbn = {{978-3-941645-11-0}}, keywords = {{High gloss, surface measurement, topographic features, quality assessment}}, location = {{Trieste, Italy}}, number = {{1}}, pages = {{99--110}}, title = {{{Development of an Algorithm for Measuring the Quality of High Gloss Surfaces Correlated to Human Perception}}}, year = {{2015}}, } @inproceedings{597, abstract = {{This paper is aimed to discuss current research using data mining techniques and industry statistics in production environments. The general research approach is based on the idea of using data mining processes and techniques of industry statistics to find rare and hidden patterns behind failures of complex components. A case study will be applied to illustrate how the technique is carried out and where the limits of this approach occur. The case study deals with a component supplier of printing machines, which received an increasing number of client complaints, all related to one distinct problem. The observed failures seem to occur only among clients with very high quality standards. The affected component undergoes a very complex production process with several steps in different departments. Every single production unit records data information from multiple process variables and at different points in time. In the beginning there was no understanding of the failure causes in production at all. Therefore a huge amount of production data had to be analyzed to find the pattern that discloses the failure. The data mining process starts with a first step in which the given data sets are prepared and then cleaned. Followed up by building a prediction model. The aim is to detect the root causes for failures and to predict potential failures in affected components. This paper shows how to use data mining to get the answer on pressing production failures. }}, author = {{Scheideler, Eva and Ahlemeyer-Stubbe, Andrea}}, booktitle = {{Production engineering and management : proceedings, 5th international conference, October 1 and 2, 2015, Trieste, Italy}}, editor = {{Padoano, Elio and Villmer, Franz-Josef}}, isbn = {{978-3-941645-11-0}}, keywords = {{Data mining, production failure, multi-variant analysis, multivariate process control, predictive modelling, case study}}, location = {{Trieste, Italy}}, number = {{1}}, pages = {{163--174}}, publisher = {{Hochschule Ostwestfalen-Lippe}}, title = {{{Data Mining: A Potential Detector to Find Failure in Complex Components}}}, year = {{2015}}, } @inproceedings{598, abstract = {{The aerospace sector is characterized by long product life cycles and a need for lightweight design. Additive manufacturing is a technology that produces parts layer by layer and thus enables the manufacturing of any complex parts at nearly no extra costs. A topology optimization enhances the part’s performance for their special purpose. The results are often complex bionic structures that cannot be produced with conventional manufacturing technologies. The paper analyzes how the high potential of this technologycan be applied to aerospace parts. A topology optimization will be conducted for an aircraft part explaining the crucial points and a life cycle analysis examines the achieved sustainable improvements for the aircraft’s life cycle. }}, author = {{Huxol, Andrea and Villmer, Franz-Josef}}, booktitle = {{Production Engineering and Management}}, editor = {{Padoano, Elio and Villmer, Franz-Josef}}, isbn = {{978-3-941645-11-0}}, keywords = {{Additive manufacturing, topology optimization, aerospace, life cycle costs}}, location = {{Trieste, Italy}}, number = {{1}}, pages = {{207--218}}, title = {{{Hybrid Manufacturing Machines: Combining Additive and Subtractive Manufacturing Technologies}}}, year = {{2015}}, } @inproceedings{599, abstract = {{Order picking has long been identified as the most labor costly and intensively activity in warehouse management. The orders from the customers need to be fulfilled tightly and timely. In order to keep the required high service level, the warehouse has to increase the picking productivity under the constraints of limited capacity. This paper concerns a man-togoods order picking system, in which the order pickers have to drive with a pallet jack to the storage locations. Considering that the orders are mostly small orders which consist of less lines, it is efficient to combine severalsingle customer orders into one picking order. Under this circumstance, this paper intends to answer the question of how customer orders should be grouped into picking orders with the aim of minimizing the total travel length through the warehouse. Consequently the productivity of the order picking system can be improved. An optimization problem for order batching is introduced. The optimization method of order batching is then proposed. Based on the simulation of different scenarios of incoming orders, it can be concluded that the developed method is effective in improving the productivity of the concerned order picking system. }}, author = {{Li, Li and Schulze, L.}}, booktitle = {{Production Engineering and Management}}, editor = {{Padoano, Elio and Villmer, Franz-Josef}}, isbn = {{978-3-941645-11-0}}, keywords = {{Order picking, man-to-goods, order batching, picking productivity, genetic algorithm}}, location = {{Trieste, Italy}}, number = {{1}}, pages = {{319--326}}, title = {{{Improving the Productivity of a Man-to-Goods Order Picking System through Optimization of Order Batching}}}, year = {{2015}}, } @proceedings{335, abstract = {{The University of Trieste (Università degli Studi di Trieste) and the Ostwestfalen-Lippe University of Applied Sciences introduced the International Double Degree Master Program ‘Production Engineering and Management’ in 2011. Its aim is to give students in Italy and Germany, along with other countries, the chance to learn the necessary abilities from lecturers and each other. This Master Program has been accompanied by the International Conference ‘Production Engineering and Management’ from the very beginning. The annual International Conference on Production Engineering and Management took place for the fifth time this year, and can therefore be considered a well-established event originating from the partnership between the University of Trieste (Italy) and the Ostwestfalen-Lippe University of Applied Sciences (Germany). The main aim of the five conferences has been to bridge the gap between production engineering and management theory and practice, by offering a platform where academia and industry could discuss practical and pressing questions. In this respect, the fifth conference (PEM 2015) continues along the same path of the first four successful conferences, which were held in Pordenone (2011), Lemgo (2012), Trieste (2013) and again in Lemgo (2014). PEM 2015 benefited further from contributions from other universities and from research and industry projects. Especially the contributions of successful graduates of the double degree Master’s program Production Engineering and Management and those of other postgraduate researchers from several European count ries have been enforced in this year. The title ‘An active interaction between university and industry’ introduced two years ago to emphasize lively cooperation proved to be more than appropriate in the conference’s main orientation: • To present current research projects and their results at a highly sophisticated scientific level • To discuss recent developments in industry and society • To bring professionals, specialists and students together • To enable professionals, lecturers and professors to exchange experiences • To familiarize young professionals and students with scientific conference procedures • To give postgraduate and Ph.D. students the chance to present a paper • To show the two partner regions’ uniqueness and performance • To attract students for an international career in the industry • To encourage students to be open-minded about different cultures, mentalities and manners PEM 2015 took place between October 1 and 2, 2015 at the University of Trieste. The program was defined by the Organizing and Scientific Committees and clustered into five scientific sessions. Both universities and their partner organizations debated on these topics by reporting their research, experiences and success stories. The scientific sessions dealt with technical and engineering issues, as well as management topics, and included contributions by researchers from academia and industry. The extended abstracts and full papers of the contributions underwent a double-blind review process. The 35 accepted presentations were assigned, according to their subject, to one of the following sessions:, ‘Industrial Engineering and Lean Management’, ‘Technology and Supporting Services for Manufacturing’, ‘Product Lifecycle, from Concept to Market and Use’, ‘Supply Chain Design and Management’ and ‘Management Practices and Methodologies’. These sessions have been carefully selected by the organizing and scientific committees and are aimed at highlighting some of the current production industry’s most discussed topics. Therefore, the articles sustainability and revolutionary developments in modern industry and cover not only production in a narrower sense, but also new aspects of: innovation and product development, of supply chains, of quality improvement. The proceedings have been drawn together to form 35 full papers of the scientific contributions. The articles were reviewed by the Scientific Committee before being accepted. As the editors of the proceedings, we would like to thank all contributors, the referees who accepted the burden of reviewing the abstracts as well as the full papers and the members of the Organizing Committee and Scientific Committee for planning such an effective conference.}}, editor = {{Padoano, Elio and Villmer, Franz-Josef}}, isbn = {{978-3-941645-11-0}}, location = {{Trieste, Italy}}, number = {{.}}, pages = {{418}}, title = {{{Production Engineering and Management}}}, volume = {{11}}, year = {{2015}}, } @proceedings{589, editor = {{Villmer, Franz-Josef and Padoano, Elio}}, isbn = {{978-3-941645-10-3}}, location = {{Lemgo}}, pages = {{301}}, title = {{{Production Engineering and Management}}}, volume = {{10}}, year = {{2014}}, } @proceedings{725, editor = {{Padoano, Elio and Villmer, Franz-Josef}}, isbn = {{978-3-941645-09-7}}, location = {{Trieste, Italy}}, pages = {{282}}, title = {{{Production Engineering and Management}}}, volume = {{9}}, year = {{2013}}, }