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  • 201.
    Wallin Johansson, Daniel
    University of Skövde, School of Engineering Science.
    KARTLÄGGNING AV VÄRDEFLÖDEOCH IDENTIFIERING AV SLÖSERIERFÖR ÄGGPRODUKTION2019Independent thesis Basic level (university diploma), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    Dava Foods in Skara has been the industry for this final year project where they processing egg in different conditions. For this project has the process where they manufacture protein drinks as they sold to the stores been in focus. The main goals for the project were to bring a value streaming map of the current state of the production and suggest improvements based on this map. The second goal was to find which types of wastes that occur and find improvements.

    To create an understanding of the existing process, an analysis was made where the stream was observed. Observations and interviews were used to collect data for the project. The analysis of the exciting process has been based on for the implementation stage.

    During the implementation stage was different tools used to collect data. PDCA has been a tool where was followed during the whole project. The value streaming map has been a central tool which was used to bring out a value streaming map. To collect the times which was needed for the value streaming map a stopwatch was used.

    The project result in different improvement proposal where many of the proposals included was to automate the processes. One solution was to change the operator against a robot cell which would streamline the process which would result in a lower throughput. Change machine was another solution where many stops occur. A full automation concept was suggested to combine these two suggestions, where both a robot and a machine was bought. The last suggestion of the value streaming map was about to just produces one product at a time. Within the wastes were three suggestions given where maintenance was the best solution to reduce the wastes. To determine which one of the suggestions was the best solution a pick chart was used to priority how hard the suggestion was and benefit.

    The conclusion was to purchasing the machine where stops frequently occur. This suggestion would create a higher efficiency in the production at the same time where the condition about price would give the best solution. Improvements of maintenance would also result as the best solution to increase the efficiency for the current machines and reduce the number of stops.

  • 202.
    Wang, Wei
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Bandaru, Sunith
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Sánchez de Ocãna Torroba, Adrian
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Improved Human-Robot Collaboration Through Simulation-Based Optimization2019In: Advances in Manufacturing Technology XXXIII: Proceedings of the 17th International Conference on Manufacturing Research, incorporating the 34th National Conference on Manufacturing Research, 10–12 September 2019, Queen’s University, Belfast, UK / [ed] Yan Jin, Mark Price, Amsterdam: IOS Press, 2019, Vol. 9, p. 153-158, article id 10.3233/ATDE190027Conference paper (Refereed)
    Abstract [en]

    In order to pursue the dream combination of human flexibility and robot automation, human robot collaboration (HRC) is increasingly being investigated through academic research and industrial scenarios. HRC involves several challenges ranging from safety and comfort of the human to process efficiency and cost of robot operation. Achieving the right balance between these aspects is critical to implementing a safe, profitable and sustainable HRC environment. In this paper,we propose the use of simulation-based optimization (SBO) for assembly task allocation and scheduling for a HRC working cell in which an industrial robot assists a human worker. The list of product assembly operations are classified according to the capability of human worker and robot, and the sequencing constraints on them are the initial inputs of the method. The operators’ ergonomic load scores and cycletime of the assembly process are achieved by simulation. The optimized solutions are sorted to find the trade-offs between ergonomics and cycle time. We demonstratethe feasibility of the proposed approach through an industrial case study.

  • 203.
    Wiktorsson, Magnus
    et al.
    KTH Royal Insitute of Technology, Dept of Sustainable Production Development, Södertälje, Sweden.
    Noh, Sang Do
    Sungkyunkwan University, Dept of Industrial Engineering, Suwon, South Korea.
    Bellgran, Monica
    KTH Royal Insitute of Technology, Dept of Sustainable Production Development, Södertälje, Sweden.
    Hanson, Lars
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre. Scania CV, Global Industrial Development, Södertälje, Sweden.
    Smart Factories: South Korean and Swedish examples on manufacturing settings2018In: Procedia Manufacturing, E-ISSN 2351-9789, Vol. 25, p. 471-478Article in journal (Refereed)
    Abstract [en]

    What constitutes a company's capabilities to develop a Smart Factory? South Korean and Swedish perspectives are here illustrated by company examples of smart factory solutions and related strategic aspects of their digitalization. It is concluded that the "smart-factory-capability" of a manufacturing company is integrated with its corporate production systems and includes perspectives on application areas, value adding processes as well as enabling technologies. It is furthermore challenged by the transformational inabilities of legacy systems. By its concrete examples is use and financial benefits, the paper contributes to the definition of the smart factory and its corresponding development scheme. 

  • 204.
    Wänerberger, Alexander
    et al.
    University of Skövde, School of Engineering Science.
    Said, Sayyed Hamid
    University of Skövde, School of Engineering Science.
    Lagerstyrning och prognostisering av råmateriallagret2014Independent thesis Basic level (university diploma), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Production to customer order usually requires keeping a supply warehouse. Increased customer demands for short lead-times require that materials must be in stock. This result in increasing stock levels in a company leads to more capital tied up and simultaneously leads to poorer yields. To avoid keeping a large storage warehouse whilst keeping a good service requires an effective inventory control.

    The purpose of this project is to find out how the demand looks like in the current situation of the company and to develop an appropriate forecasting method and calculation model against a certain pace for inventory control. The methods mentioned in this work are the ABC analysis, calculation of safety stock and forecasting methods.

    The results from this work will answer the objectives of the project aims. A variety of analyzes and experiments shall be used to investigate what type of forecasting method that the company should use. The methods and theories raised in the report also aims to be used by similar companies. The aim of the selected forecasting method is also to lead to a better base, from which better forecast precision is one part in order to improve the inventory management. This has, as far as possible, been put in relation to the working methods used in the company today. Some of the work has been to find out how much demand changes during the lead times, i.e. from the ordering of raw material until the material is in the raw material stock. This has also been used to compare forecasting methods against the present approach.

    Because the company wants to expand its production, a calculation model has also been developed. This model indicates the inventory level to a desired pace, i.e. demand level.

  • 205.
    Xia, Johnny
    University of Skövde, School of Engineering Science.
    A NEW STUDY OF UNBALANCED PRODUCTION LINE WITH OPTIMIZATION2018Independent thesis Basic level (degree of Bachelor), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    This project is a continuous research of a topic well-known in the literature, namely, the performance study of unbalanced unpaced production system. In the literature, there were many studies that investigated the statistical outputs of an unbalanced production line using simulation. This project focuses on researching the outputs like average buffer level and idle time that are rarely studied in previous research by using optimization tools from discrete event simulation software FACTS.The models used in the article (Shaaban & McNamara, 2009) have been used as a guideline during the development of the simulation models for this project. Two simulation models were created, each using different discrete event simulation software, namely FACTS analyzer and Plant simulation. Those simulation models fulfills its role in verification & validation stage, with their statistical outputs compared to each other and with Shaaban and McNamara’s results. After verification & validation comes optimization of those simulation models, by using optimization tools from FACTS.The research area expanded during the optimization phase. Originally Shaaban et.al analyzed unbalanced production line with one fixed value of coefficient of variation. In order to expand the view on the properties of an unbalanced production line, three more coefficient variation were added with total of four in this project. As a result, 12 optimization results were created at the end of this project. Each optimization has 30 000 iterations to ensure its convergence.The first step of analysis is done by locating all Pareto-optimal solutions with optimization tools in FACTS. The raw data of all solutions are later transferred and converted into EXCEL files. Using scatter graph and putting all outputs against each other in EXCEL, it creates visual graph that can be used to analyze and to investigate interesting behavior in an unbalanced production line.The analysis on the optimization results showed several interesting behaviors from production line with different settings. One being that if a production line possess worse coefficient of variation than its competition. By raising the inter-stage buffer level of the production line with inferior coefficient of variation, it can achieve the same level, if not greater outputs than its competitor who possess better coefficient of variation. The other interesting behavior are optimization results with highest outputs in regard of either idle time or average buffer level, with deep analyzation using optimization tools from FACTS. Certain operation time pattern and inter-stage buffer pattern could be observed from those results.

  • 206.
    Yousefi, Milad
    et al.
    Department of Production and Transportation Engineering, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil.
    Yousefi, Moslem
    Department of Mechanical Engineering, Islamic Azad University, Roudehen Branch, Roudehen, Iran.
    Fathi, Masood
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Fogliatto, Flavio
    Department of Production and Transportation Engineering, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil.
    Patient visit forecasting in an emergency department using a deep neural network approach2019In: Kybernetes, ISSN 0368-492X, E-ISSN 1758-7883Article in journal (Refereed)
    Abstract [en]

    This study aims to investigate factors affecting daily demand in an emergency department (ED) and to provide a forecasting tool in a public hospital for horizons of up to 7 days.In this study, first the important factors to influence the demand in EDs were extracted from literature then the relevant factors to our study are selected. Then a deep neural network is applied for constructing a reliable predictor.Although many statistical approaches have been proposed for tackling this issue, better forecasts are viable through employing the abilities of machine learning algorithms. Results indicate that the proposed approach outperforms statistical alternatives available in the literature such as multiple linear regression (MLR), autoregressive integrated moving average (ARIMA), support vector regression (SVR), generalized linear models (GLM), generalized estimating equations (GEE), seasonal ARIMA (SARIMA) and combined ARIMA and linear regression (LR) (ARIMA-LR).We applied this study in a single ED to forecast the patient visits. Applying the same method in different EDs may give us a better understanding of the performance of the model. The same approach can be applied in any other demand forecasting after some minor modifications.To the best of our knowledge, this is the first study to propose the use of long short-term memory (LSTM) for constructing a predictor of the number of patient visits in EDs.

  • 207.
    Zia, Muhammad Irfan
    et al.
    University of Skövde, School of Technology and Society.
    Cortés Mora, Felipe
    University of Skövde, School of Technology and Society.
    Automation of packing process2008Independent thesis Basic level (degree of Bachelor), 15 credits / 22,5 HE creditsStudent thesis
    Abstract [en]

    The design work that precedes the automation of a process is not an easy job. Each one of the variables and possible risks involved in process must be carefully considered before implement the final design as well the requirements in performance and cost. However automate a dangerous, inefficient or just uncomfortable task entails many benefits that make up for the long period of design process. A well automated line will benefit the production with quality, productivity and capacity among other profits. In this project the immediate objective is to automate the “SANDFLEX Hacksaw blades” packaging process in the plant that SNAEurope owns in Lidköping. Actually the packing is completely manual. One operator packs the blades into the boxes meanwhile one more operator loads and unloads the packing station with empty and full boxes respectively. The task is both, tiring and uncomfortable for the operators as well inefficient for the company since the production rate is limited.

    Analyzing and observing carefully product and process, different theories and strategies to achieve the goal were developed. Three are the possible solutions to solve the problem, with different levels of automation and technologies. The robotic solution uses an articulated robot to perform all the tasks; the hybrid solution uses pneumatic devices to pack the blades and an articulated robot to support the station loading and unloading the boxes. Finally the pneumatic solution uses only pneumatic devices, which hold, open and close, push box and blades using airpower; a few sensors detect positions and states, since a PLC coordinates and controls all process. By means of discussing these solutions with the company’s engineers and workers, after a deep literature study and two test of performance, was it possible to select the most suitable solution to accomplish the packaging task. The pneumatic solution is cheap and simple, but at the same time robust and reliable. This design performs the packaging task efficiently and fast. And more important, the operator passes from pack manually the blades to monitor the process.

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