The model is particularly designed for allocation of potatoes from several farms to a nearby starch mill, which produces starch from a limited amount of potatoes each day. Scheduling should determine how much amount of potatoes be sent from which farm to the mill on each day. It is known that the quality of potatoes decreases over time and as a result less starch is produced. A model predictive control approach is proposed to maximize the production of starch. Simulation experiments indicate that predictive scheduling can yield higher starch production compared to non-predictive approaches.
Processes in manufacturing and logistics are characterized by a high frequency of changes and fluctuations, caused by the high number of participants in logistic processes. The heterogeneous landscape of data formats for information storage further complicates efforts to automatically extract process models from this data with the tools from Process Mining. This article introduces a concept for constantly updating process models in logistics, called Process Maintenance, collects requirements for a common view on information in logistics, and shows that Process Mining with logistic data is possible, but still needs improvement to become a regular practice.
The objective of this study is to investigate supply chain performance with a focus on transport logistics. The expected effects and capacity of potential changes in supply chain performance should be taken into account while developing a management decision on logistics network functioning. It is shown that a combination of these two factors leads to the overall synergistic effect with increased output. Automation always plays an important role in industry. Today, it is a basic need for industry. To develop faster manufacturing or delivery, automation is an important need.
Robots always play the main role for automation in the industry. Robots are mainly designed for specific task. But, the main problem is robots are too expensive for one task. Thats why, it is almost impossible to use robots for small industries. Therefore, we are aiming to develop a pipeline to design a multitasking robot, especially for different kinds of packaging tasks.
Typical text-based instruction sheets are the main source of these automation robots, that means robots can pack different types of shapes using typical text-based packaging instructions. In robotics, learning by demonstration in robotics, could benefit from large body movement dataset extracted from textual instructions. The interpretations of instructions for the automatic generation of the corresponding movements thereof are difficult tasks.
We examine methods for converting textual surface structures into the semantic representations and explore tools for analysis and automated simulation of activities in industrial and household settings. In our first step, we try to develop a pipeline from textual instructions to virtual actions that includes traditional language processing technologies as well as human computation approaches. Using the resulting virtual actions, we will train robots through imitation learning or learning by demonstration for multitasking packaging robots. Transport risks in supply chains have increasingly lead to significant capital losses.
Insurance claims against such losses have grown accordingly, while simultaneous advances in technology lead to continuously larger volumes of data recorded. Traditional risk evaluation methods in insurance struggle to account for rising supply chain complexity which is reflected by growing amount and dimensionality of supply chain data. Therefore decision-makers in the transport insurance industry need new ways of appropriate knowledge representation to support transport insurance providers with daily tasks such as premium tariffing. This paper presents a method based on multidimensional scaling MDS for the identification of groups of similar claims as a first step towards the improvement of supply chain risk evaluation and forecasting.
We show the application potential of transforming and visualising transport damage claims data as the basis for developing decision support systems DSS to support transport insurance providers in tasks such as premium tariffing as well as transport and supply chain managers in risk mitigation and prevention activities. The purpose of this study is to develop and demonstrate a semi-automated text analytics approach for the identification and categorization of information that can be used for country logistics assessments.
In this paper, we develop the methodology on a set of documents for 21 countries using machine learning techniques while controlling both for 4 different time periods in the world FDI trends, and the different geographic and economic country affiliations. Implications are discussed and future work is outlined. The aim of this study is to discuss the characteristics of the input data to the data analytical algorithms of a predictive maintenance system, from the viewpoint of big data technology.
The discussed application is for the maintenance of off-shore wind turbines. The maintenance of off-shore wind turbines is an expensive and sensitive task. Therefore, making decision for planning and scheduling of maintenance in a wind farm which is made by the operating company of a wind farm is important and plays a critical role in the cost of maintenance.
In this paper, the current state of the art for big data technology in the maintenance of off-shore wind turbines is presented. The dimensions of big data analytics and the technical requirements of data for the use of this technology in the maintenance of off-shore wind turbines are described. A contribution of this paper is to study the technical requirements of suitable data for decision-making.
The outcomes of presented study are identifying the characteristics of input data to predictive maintenance in the era of big data and the discussion of these characteristics in the condition monitoring for off-shore wind energy. The objective of this study is to investigate an optimal vehicle routing scheme to perform an OEM milk-run pickup service over a regional road network. The manufacturing of components is subject to varying tardiness among suppliers when fulfilling OEM orders.
This often leads to non-accomplished orders at the end of the vehicle cycle time since the transport operation, predominantly composed by random variables, must comply with a strict delivery time limit set up by the OEM company.
The mathematical model searches for the optimal vehicle routing sequence, together with searching for the best tardiness tolerance level that minimizes the sum of penalty costs levied against faulty suppliers, and transport expenses. Supply chain risk management process SCRMP is being advanced as a systematic and structured approach for identifying, assessing, mitigating, and monitoring all risks arising from complex supply chains.
However, while the literature deems it necessary to implement such a process as the solution to the increasing vulnerability companies face, there is a lack of empirical evidence on whether the process model can be implemented. This paper shows possible hindrances in the implementation of SCRMP for companies with global supply chains based on the findings of an in-depth case study. Our empirical findings indicate that the unavailability of information and lack of proper data management hinders the implementation of SCRMP in the context global supply chains.
This paper focuses on different aspects of fashion markets. In a first step, fashion levels will be classified; followed by definitions on fashion trends, and the suggestions on a fashion trend concept.
In order to fill this concept and support decision-making processes along the supply chain, such as the catching of actual fashion trends, it is required to fill this concept with relevant information on different product features. Social media text data is considered as one relevant source. Showing previous researches, we assume that for instance fashion weblogs can be used for extracting this information. In a further step, we describe different fashion markets, namely fast fashion and luxury, in order to examine the applicability of the approach to real-life markets and their supply chain processes.
The paper concludes by formulating hypotheses on a potential application of the approach. In developing countries, significant food losses occur during distribution. The use of technologies such as Intelligent Packaging IP and the Internet of Things IoT may provide improvements in controlling the distribution of food products, minimizing losses. This paper identifies the Brazilian food supply chains current technological state and their receptivity to the IP and IoT technologies adoption. The results show that these companies do not currently use IP and that a few use what they consider to be IoT systems.
Cost is the greatest barrier to the use of these technologies; however, the lack of knowledge about these technologies also represents a strong barrier to their use. With the evaluation of new applications, new goals regarding efficiency and security have been added for logistics and general user application, which demand time-bounded and reliable services.
We simulated VANET by considering different application scenarios for logistics and transportation using varying parameters such as speed, number of nodes, traffic load and bit error rate etc. We observed that it performs well in most of the scenarios due to its highly suitability in vehicular environment. Smartphones provide rich applications and offer many crowdsensing services to end users. However, the power consumption of smartphones is still a primary issue in green computing. This paper presents a general power management framework including a data logger, an unsupervised learning algorithm of classifier, and a power-saving decision maker.
The framework gathers and analyses the usage patterns of smartphones and separates end users into non-active and active ones, and their mobile devices into low-power ones and high-power ones using an unsupervised learning algorithm. If the smartphone of a non-active user belongs to the high-power group, we observe abnormal usage behaviour. The framework provides recommendations, e. We collected device usage and power consumption attributes on two kinds of Android—smartphones and evaluated the framework in experimental studies with 22 users.
In this paper, a prototype is developed, which can easily integrate a wireless sensor with programmable logic controllers PLC using Profinet. A Wizziboard wireless sensor node, running the Dash7 communication protocol, periodically sends temperature and humidity data. The data is transferred using the Ethernet bus. Data logging is also implemented in the HMI software.
The benefits of remote monitoring of perishable food items in transport and storage of a cool chain have been established and much talked about in the past decade. In order to convey the measured parametric data over for processing, wireless sensor networks are used, mostly in 2. This paper analyzes the possibility of wireless communication in MHz and its lower sensitivity to water containing environments by means of a case study in an apple storage warehouse.
The experiment shows near conformity to a previously implemented theoretical model of signal attenuation, the only error being due to ca. Second, the papers focuses on practical experiments with the focus on the DASH7 protocol, which is dedicated to sub-GHz communication, the OSS-7 software stack, and a multi-sensor, small-footprint hardware platform. In horizontal coalitions for auction-based exchange of transportation requests, freight carriers have to identify requests that are selected for offering to coalition partners.
Small- and medium-sized forwarders are confronted with thin margins and high demand fluctuations in competitive transportation markets. In these markets forwarders try to improve their planning situation by using external resources besides their own resources. These external resources might belong to closely related subcontractors, common carriers or cooperating forwarders in horizontal coalitions. In recent publications, it is assumed that some transportation requests are prohibited to be fulfilled by certain external resources due to contractual obligations.
These requests are known as compulsory requests. In this paper, a transportation planning problem including external resources is extended by the mentioned compulsory requests. It is proposed to consider different types of compulsory requests depending on the applicable external resources for fulfilling these requests. As a solution approach a column generation-based heuristic is applied, which uses a strict composition procedure and a strict generation procedure for handling compulsory requests. In a detailed computational study, the increase of transportation costs is analyzed. Commercial vehicles are a common mode of transport employed in the urban freight transport.
Normally, they are internal combustion engine ICE vehicles powered by burning fossil fuels. However, with deteriorating air quality and decreasing energy resources, ICE vehicles are experiencing a significant transition. Electric commercial vehicles ECVs as a feasible alternative to alleviate emissions and save energy resources are proposed in the field of urban freight transport. Therefore, this paper reviewed and analyzed 25 related articles to collect factors affecting the employment.
Furthermore, we classified the factors into the three pillars of sustainability with integrating technological dimension. The results illustrate the influence of positive factors and negative factors on the employment.
5th LDIC 2016: Bremen, Germany
The future work will focus on ranking the priorities of factors and suggesting the logistics company to consider ECVs in their fleets thereby improving the adoption and the sustainable urban freight transport. Integrated operational transportation planning IOTP refers to the extension of vehicle routing by the option of subcontraction.
In practice, planners often use semi-manual strategies for IOTP. Two wide spread semi-manual strategies for IOTP are presented. The strategies are evaluated by computational experiments comparing the results achieved by these strategies with the exact solutions which have been provided by MIP approach for IOTP. This paper presents a state-of-the-art analysis of Intelligent Transport Systems ITS for road freight transport including an overview of telematics applications for road freight transport. Furthermore, an analysis on how different actors of a transport chain perceive the developments of ITS is given.
The paper also presents selected examples of practical ITS usage. Researchers intend to employ emission trading scheme ETS as one of the cost-effective policy instruments on the level of supply chains SCs to control SC emissions. Through analyzing mathematical models adopted in available literatures to address the implementation, it identifies the intentions and approaches of imposing ETS in the context of SCs.
- Lehrstuhl für Allgemeine Betriebswirtschaftslehre und Logistikmanagement.
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This paper is believed to be one of the first literature reviews in addressing ETS in the context of SCs. In the last decade, the erection of offshore wind turbines, especially in the northern sea, has been showing a significant growth and this trend will continue further in the next years. In order to make the offshore wind energy competitive and attractive, the different processes related to the overall life cycle cost of an offshore wind farm have to be optimized. Thereby, the efficiency of the maintenance processes is a crucial factor to guarantee sustainable energy and improve the reliability and availability of an offshore wind turbine.
Indeed, the maintenance activities in the offshore field are a challenging task especially due to the harsh maritime environment which leads to high material stress and low resource utilization. In this paper, we model the maintenance processes of an offshore wind farm by means of a discrete event and agent -based simulation model. The objective is to schedule the maintenance tasks taking into account all real restrictions based on historical data in order to determine important factors and potential operational improvement.
As an example, the simulation will be used to determine the optimal number of resources needed to perform maintenance activities by keeping the resource utilization in an acceptable level. This paper discusses the process model of consumer logistics by Granzin and Bahn from the perspective of the shopper. Thereby, we propose a model of shopper logistics and provide further insight into the planning and execution of shopper logistics based on an empirical study amongst private households.
Our findings identify a distinction between planning and executing logistics activities which are not performed in a sequential but in a simultaneous manner. The repositioning of empty containers is one of the most important tasks in container shipping. Manish Govil.
Shop Dynamics In Logistics Proceedings Of The 4Th International Conference Ldic Bremen Germany
Shigeki Umeda. Management Innovations for Intelligent Supply Chains. John Wang. Internet of Things. IoT Infrastructures. Raffaele Giaffreda. Springer Handbook of Automation. Shimon Y. Information Systems for the Fashion and Apparel Industry.
Dynamics in Logistics
Tsan-Ming Jason Choi. Planning Production and Inventories in the Extended Enterprise. Karl G Kempf. Maintenance Management in Network Utilities. Ershi Qi. Markus Helfert. Project Management with Dynamic Scheduling. Mario Vanhoucke. Successes and Failures of Knowledge Management. Jay Liebowitz. Critical Information Infrastructures Security. Marianthi Theocharidou. Klaus Altendorfer. Supply Chain Optimization, Management and Integration.
Honglei Xu. Intelligent Non-hierarchical Manufacturing Networks. Raul Poler. Efficiency and Innovation in Logistics. Uwe Clausen. Advances in Sustainable and Competitive Manufacturing Systems. Logistics and Supply Chain Innovation. Henk Zijm. Operative Transportation Planning. Thorben Seiler. Robust Manufacturing Control. Katja Windt.
Alberto Leon-Garcia. Reliability and Statistics in Transportation and Communication. Igor Kabashkin. Paulina Golinska. Industrial Internet of Things. Sabina Jeschke. Unique Radio Innovation for the 21st Century. Sherali Zeadally. EcoProduction and Logistics. Advances in Through-life Engineering Services. Louis Redding. Kari T. Runliang Dou. Engineering Asset Management Joseph Mathew. Theodor Borangiu. Big Data Analytics with R and Hadoop.
Vignesh Prajapati. Service Science, Management, and Engineering:. Gang Xiong. Arup Nanda. Joe Amadi-Echendu. Fundamentals of Discrete Math for Computer Science. Ben Stephenson. Taylor Pierce. Pawel Pawlewski. TensorFlow Machine Learning Cookbook. Nick McClure. David C. Digital Marketplaces Unleashed. Michael Zaddach. Advanced Computing Strategies for Engineering. Ian F. Spark: The Definitive Guide. Bill Chambers. Information Technology in Environmental Engineering. Burkhardt Funk. Sukant Pandey. Jerzy Pokojski. Automatic Speech Recognition. Dong Yu. Business Information Systems Workshops.
Witold Abramowicz. Thomas D. Michael Sonnenschein.
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Apache Kafka 1. Sandeep Khurana. Ramy Harik. Learning Social Media Analytics with R. Raghav Bali. Emergency Response Decision Support System. Siqing Shan. Hadoop: Data Processing and Modelling.