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The Experts below are selected from a list of 90 Experts worldwide ranked by ideXlab platform

Regina Nickel - One of the best experts on this subject based on the ideXlab platform.

  • eco design in the printing industry life cycle thinking implementation of eco design concepts and tools into the routine procedures of companies
    The Journal of Sustainable Product Design, 2003
    Co-Authors: Ursula Tischne, Regina Nickel
    Abstract:

    For some years, the printing industry has been faced with environmental problems like emissions of waste volatile organic compounds (VOCs) and other hazardous substances. A lot has been done to eliminate these end-of-pipe problems. One project, focused on opportunities to optimise the environmental features of prepress and printing Machines at an early stage of the life cycle e.g. the design phase, is discussed in this text. Under the heading of the ‘Implementation of Eco-design Concepts in Companies of the Machine Engineering Industry’ the project was carried out by econcept and Europe’s largest printing Machine Manufacturer Heidelberger Druckmaschinen AG. with the support of the German Environmental Foundation (Deutsche Bundesstiftung Umwelt, DBU) was planned as a test case for implementing eco-design in small and medium sized enterprises (SMEs) and the main activities were concentrated on the business unit Prepress in Kiel, Germany. It aimed at developing innovative and effective tools, which were easy to implement into the usual and daily procedures of the company. During the project typical products of the business unit were analysed, an environmental handbook for product development was developed, and education programmes and information was generated for the employees, customers and waste managers. Finally, the systematic integration of knowledge and tools into the existing formalised product development process of the company lead to environmentally optimised products and financial advantages.

Darina Juhaszova - One of the best experts on this subject based on the ideXlab platform.

  • innovative methods for small mixed batches production system improvement the case of a bakery Machine Manufacturer
    Sustainability, 2020
    Co-Authors: Kristina Zgodavova, Peter Bober, Vidosav D Majstorovic, Katarina Monkova, Gilberto Santos, Darina Juhaszova
    Abstract:

    One of the common problems of organizations with turn-key projects is the high scrap rate. There exist such traditional methods as Lean Six Sigma (LSS) and DMAIC tools that analyze causes and suggest solutions. New emerging intelligent technologies should influence these methods and tools as they affect many areas of our life. The purpose of this paper is to present the innovative Small Mixed Batches (SMB). The standard set of LSS tools is extended by intelligent technologies such as artificial neural networks (ANN) and Machine learning. The proposed method uses the data-driven quality strategy to improve the turning process at the bakery Machine Manufacturer. The case study shows the step-by-step DMAIC procedure of critical to quality (CTQ) characteristics improvement. Findings from the data analysis lead to a change of measurement instrument, training of operators, and lathe Machine set-up correction. However, the scrap rate did not decrease significantly. Therefore the advanced mathematical model based on ANN was built. This model predicts the CTQ characteristics from the inspection certificate of the input material. The prediction model is a part of a newly designed process control scheme using Machine learning algorithms to reduce the variability even for input material with different properties from new suppliers. Further research will be focused on the validation of the proposed control scheme, and acquired experiences will be used to support business sustainability.

M Z Babai - One of the best experts on this subject based on the ideXlab platform.

  • demand categorisation in a european spare parts logistics network
    International Journal of Operations & Production Management, 2009
    Co-Authors: Argyrios Syntetos, M Keyes, M Z Babai
    Abstract:

    Purpose – Spare parts have become ubiquitous in modern societies and managing their requirements is an important and challenging task with tremendous cost implications for the organisations that are holding relevant inventories. An important operational issue involved in the management of spare parts is that of categorising the relevant stock keeping units (SKUs) in order to facilitate decision-making with respect to forecasting and stock control and to enable managers to focus their attention on the most “important” SKUs. This issue has been overlooked in the academic literature although it constitutes a significant opportunity for increasing spare parts availability and/or reducing inventory costs. Moreover, and despite the huge literature developed since the 1970s on issues related to stock control for spare parts, very few studies actually consider empirical solution implementation and with few exceptions, case studies are lacking. Such a case study is described in this paper, the purpose of which is to offer insight into relevant business practices. Design/methodology/approach – The issue of demand categorisation (including forecasting and stock control) for spare parts management is addressed and details reported of a project undertaken by an international business Machine Manufacturer for the purpose of improving its European spare parts logistics operations. The paper describes the actual intervention within the organisation in question, as well as the empirical benefits and the lessons learned from such a project. Findings – This paper demonstrates the considerable scope that exists for improving relevant real word practices. It shows that simple well-informed solutions result in substantial organisational savings. Originality/value – This paper provides insight into the empirical utilisation of demand categorisation theory for forecasting and stock control and provides some very much needed empirical evidence on pertinent issues. In that respect, it should be of interest to both academics and practitioners.

  • demand categorisation in a european spare parts logistics network
    International Journal of Operations & Production Management, 2009
    Co-Authors: Argyrios Syntetos, M Keyes, M Z Babai
    Abstract:

    Purpose – Spare parts have become ubiquitous in modern societies and managing their requirements is an important and challenging task with tremendous cost implications for the organisations that are holding relevant inventories. An important operational issue involved in the management of spare parts is that of categorising the relevant stock keeping units (SKUs) in order to facilitate decision-making with respect to forecasting and stock control and to enable managers to focus their attention on the most “important” SKUs. This issue has been overlooked in the academic literature although it constitutes a significant opportunity for increasing spare parts availability and/or reducing inventory costs. Moreover, and despite the huge literature developed since the 1970s on issues related to stock control for spare parts, very few studies actually consider empirical solution implementation and with few exceptions, case studies are lacking. Such a case study is described in this paper, the purpose of which is to offer insight into relevant business practices. Design/methodology/approach – The issue of demand categorisation (including forecasting and stock control) for spare parts management is addressed and details reported of a project undertaken by an international business Machine Manufacturer for the purpose of improving its European spare parts logistics operations. The paper describes the actual intervention within the organisation in question, as well as the empirical benefits and the lessons learned from such a project. Findings – This paper demonstrates the considerable scope that exists for improving relevant real word practices. It shows that simple well-informed solutions result in substantial organisational savings. Originality/value – This paper provides insight into the empirical utilisation of demand categorisation theory for forecasting and stock control and provides some very much needed empirical evidence on pertinent issues. In that respect, it should be of interest to both academics and practitioners.

Hilgenberg Kai - One of the best experts on this subject based on the ideXlab platform.

  • In-Situ Defect Detection in Laser Powder Bed Fusion by Using Thermography and Optical Tomography—Comparison to Computed Tomography
    2020
    Co-Authors: Mohr Gunther, Altenburg, Simon J., Ulbricht Alexander, Heinrich Philipp, Baum Daniel, Maierhofer Christiane, Hilgenberg Kai
    Abstract:

    Among additive manufacturing (AM) technologies, the laser powder bed fusion (L-PBF) is one of the most important technologies to produce metallic components. The layer-wise build-up of components and the complex process conditions increase the probability of the occurrence of defects. However, due to the iterative nature of its manufacturing process and in contrast to conventional manufacturing technologies such as casting, L-PBF offers unique opportunities for in-situ monitoring. In this study, two cameras were successfully tested simultaneously as a Machine Manufacturer independent process monitoring setup: a high-frequency infrared camera and a camera for long time exposure, working in the visible and infrared spectrum and equipped with a near infrared filter. An AISI 316L stainless steel specimen with integrated artificial defects has been monitored during the build. The acquired camera data was compared to data obtained by computed tomography. A promising and easy to use examination method for data analysis was developed and correlations between measured signals and defects were identified. Moreover, sources of possible data misinterpretation were specified. Lastly, attempts for automatic data analysis by data integration are presented

Ursula Tischne - One of the best experts on this subject based on the ideXlab platform.

  • eco design in the printing industry life cycle thinking implementation of eco design concepts and tools into the routine procedures of companies
    The Journal of Sustainable Product Design, 2003
    Co-Authors: Ursula Tischne, Regina Nickel
    Abstract:

    For some years, the printing industry has been faced with environmental problems like emissions of waste volatile organic compounds (VOCs) and other hazardous substances. A lot has been done to eliminate these end-of-pipe problems. One project, focused on opportunities to optimise the environmental features of prepress and printing Machines at an early stage of the life cycle e.g. the design phase, is discussed in this text. Under the heading of the ‘Implementation of Eco-design Concepts in Companies of the Machine Engineering Industry’ the project was carried out by econcept and Europe’s largest printing Machine Manufacturer Heidelberger Druckmaschinen AG. with the support of the German Environmental Foundation (Deutsche Bundesstiftung Umwelt, DBU) was planned as a test case for implementing eco-design in small and medium sized enterprises (SMEs) and the main activities were concentrated on the business unit Prepress in Kiel, Germany. It aimed at developing innovative and effective tools, which were easy to implement into the usual and daily procedures of the company. During the project typical products of the business unit were analysed, an environmental handbook for product development was developed, and education programmes and information was generated for the employees, customers and waste managers. Finally, the systematic integration of knowledge and tools into the existing formalised product development process of the company lead to environmentally optimised products and financial advantages.