@misc{13675, abstract = {{This paper extends a previously developed biobjective Mixed-Integer Linear Programming (MILP) methodology for reducing electricity costs and CO2 emissions in Smart-E-Factory applications. While the earlier approach assumed fixed photovoltaic (PV) and battery capacities, we now propose a cascaded optimization framework to determine the optimal sizing (power rating and orientation of the PV system, battery capacity) while simultaneously optimizing battery dispatch. The cost function combines operational costs with amortized investment costs of both PV and battery systems, embedded in a dynamic scheduling optimization that addresses real-time electricity price and CO2 signals. Numerical results indicate that intermediate capacities and balanced east/west orientation maximize cost-effectiveness and emission reductions. This study underscores the value of coupling parametric design and dispatch optimization to achieve scalable, sustainable solutions for industrial energy systems.}}, author = {{Mousavi, Seyed Davood and Schulte, Thomas}}, booktitle = {{ 6th International Conference on Electrical, Communication and Computer Engineering (ICECCE 2025) : 27-28 August 2025, Istanbul, Türkiye}}, isbn = {{979-8-3315-4915-2 }}, keywords = {{Photovoltaic systems, Cost, Electricity, Tariffs, Stochastic processes, Real-time systems, Robustness, Batteries, Planning, Mixed integer linear programming}}, location = {{Istanbul, Turkiye }}, publisher = {{IEEE}}, title = {{{Cascaded Optimization of PV and Battery Sizing Under Dynamic Cost and CO Signals}}}, doi = {{10.1109/icecce67514.2025.11257982}}, year = {{2025}}, } @misc{13224, abstract = {{This paper presents a robust methodology for optimizing CO2 emissions and electricity costs in industrial applications, with the aim of developing a flexible and dynamic energy management strategy that balances sustainability and cost-efficiency. Addressing the growing need for sustainable and economically viable energy solutions amidst the global urgency of climate change mitigation, the proposed approach is based on dynamic energy management techniques that minimize dependence on grid electricity, which can fluctuate between energy import and export. A flexible cost function is developed to simultaneously account for CO2 emissions and electricity prices, enabling a balance between environmental impact and operational costs. The optimization framework employs Mixed-Integer Linear Programming (MILP) to derive the optimal energy management strategy, showcasing significant potential for reducing both CO2 emissions and electricity costs. Although the methodology is demonstrated in a specific industrial setting, its flexible design ensures applicability across various energy profiles and operational scenarios, making it relevant for a wide range of industrial applications.}}, author = {{Mousavi, Seyed Davood and Griese, Martin and Schulte, Thomas}}, booktitle = {{2024 International Conference on Electrical and Computer Engineering Researches (ICECER)}}, keywords = {{CO2 Reduction, Electricity Cost Minimization, Life Cycle Assessment, MILP, Smart-E-Factory, Dynamic Energy Management}}, location = {{Gaborone, Botswana }}, publisher = {{IEEE}}, title = {{{Dynamic Optimization of CO2 Emissions and Electricity Costs in Smart Factories}}}, doi = {{10.1109/icecer62944.2024.10920418}}, year = {{2024}}, } @misc{7981, abstract = {{The main purpose of bovine colostrum, being the milk secreted by a cow after giving birth, is to transfer passive immunity to the calf. The calves have an immature immune system as they lack immunoglobulins (Igs). Subsequently, the supply of good quality bovine colostrum is required. The quality of colostrum is classified by low bacterial counts and adequate Ig concentrations. Bacterial contamination can contain a variety of human pathogens or high counts of spoilage bacteria, which has become more challenging with the emerging use of bovine colostrum as food and food supplements. There is also a growing risk for the spread of zoonotic diseases originating from bovines. For this reason, processing based on heat treatment or other feasible techniques is required. This review provides an overview of literature on the microbial quality of bovine colostrum and processing methods to improve its microbial quality and keep its nutritional values as food. The highlights of this review are as follows: high quality colostrum is a valuable raw material in food products and supplements; the microbial safety of bovine colostrum is increased using an appropriate processing-suitable effective heat treatment which does not destroy the high nutrition value of colostrum; the heat treatment processes are cost-effective compared to other methods; and heat treatment can be performed in both small- and large-scale production.}}, author = {{Fasse, Sylvia and Alarinta, Jarmo and Frahm, Björn and Wirtanen, Gun}}, booktitle = {{Dairy}}, issn = {{2624-862X }}, keywords = {{bovine colostrum, bacteria, pathogens, probiotic bacteria, cost-effective processing, heat treatment, pasteurization, contamination control, immunoglobulins, enzymes}}, number = {{4}}, pages = {{556--575}}, publisher = {{MDPI}}, title = {{{Bovine Colostrum for Human Consumption - Improving Microbial Quality and Maintaining Bioactive Characteristics through Processing}}}, doi = {{10.3390/dairy2040044}}, volume = {{2}}, year = {{2021}}, } @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{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}}, } @inbook{5932, abstract = {{Groupage transports are frequently calculated based on freight rates assuming a declining rate with respect to volume and to transportation distance. This paper investigates the case of feeding many small shipments to customers via a freight forwarder network. It is argued that costs for post-carriage transport dominate other costs. Based on a theoretical estimate, simulation experiments for the case of a uniform distribution of customer locations around the subsidiary with a fixed shipment size per drop suggest that the aggregate costs grow progressively with increasing customer drop distances from the subsidiary. The resulting implications for transport modelling are discussed.}}, author = {{Boone, Nicholas and Quisbrock, Tim}}, booktitle = {{Advanced manufacturing and sustainable logistics : proceedings / 8th International Heinz Nixdorf Symposium, IHNS 2010, Paderborn}}, isbn = {{978-3-642-12461-7}}, keywords = {{cost-by-cause principle, freight forwarder, freight rates, network, overhead costs, pricing, simulation, transport}}, location = {{Paderborn}}, pages = {{332--344}}, publisher = {{Springer}}, title = {{{Modelling post-carriage transport costs in groupage networks}}}, doi = {{doi.org/10.1007/978-3-642-12494-5_30}}, year = {{2011}}, }