University of Twente Student Theses


The assesment of the implementation of the kanban and two-bin method in the logistic process of Medisch Spectrum Twente

Voort, Sophie Johanna Maria van der (2017) The assesment of the implementation of the kanban and two-bin method in the logistic process of Medisch Spectrum Twente.

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Abstract:Context Medisch Spectrum Twente is a hospital located in Enschede. In 2016, the hospital moved into a new building. Together with this move, the logistic department introduced a new order method to organize the distribution of products from the central warehouse of the hospital to the local warehouses on the hospital departments. In the old situation, the logistic employees checked the stock at every hospital department warehouse and ordered new products using a scan method. Now the products are ordered by order boards, these are located in the department warehouses. The new order method is a combination of the Kanban and the two-bin method. In the local warehouse of a department, every product is stored in two equally stock places (bins) and to every bin an order card is linked. These order cards are attached to the bins. The users on the hospital departments takes products from the first bin. When a bin is empty, the linked order card needs to be placed on the order board by the users of the hospital department and the products need to be moved from the second bin to the first bin. There are four different routes, called blue, red, white, and orange, from the central warehouse along several department warehouse for delivery of ordered products. The system reads out the order boards of each route at a fixed time every weekday. On that moment the products are ordered in the central warehouse. The delivery of the four routes is performed one after the other. CRQ One year after the introduction of this new method, there is a need to know how it performs. The main focus of this research is to objectify the new order method performance. Additionally, we focus on the performance improvement and control. We qualitatively analyse the suggested improvements. However, a full quantitative analysis is outside the scope of this research. Therefore, we use the following research question. How can the new order method be monitored and improved? What data and Key Performance Indicators (KPIs) are relevant to measure how the new order method performs? Method In this research we analyse the new process using the DMAIC cycle. First, we carry out a literature study to the effectiveness of the use of Lean management and the corresponding DMAIC cycle. Based on the literature search we define the current situation using our own observations, including interviews with the users of this new method. As a result of these interviews, we set up the following objectives for the new order method performance: good response time, short waiting time, correct stock level in the department warehouses, low workload, well working technology, well organized communication, and well furnished hospital department warehouses. We find 49 KPIs to asses the performance of the project objectives. In this report we focus on the KPIs delivery time, out-of-stock moments, and order card and order board errors. These KPIs are considered the most important for the users to ensure patient care. We measure and analyse these KPIs by creating multiple data warehouses with data from the two systems involved in the hospital’s logistics processes, Oracle and Alltrack. In this research we use data from the months November and December 2016, and January 2017. After the analysis we investigate how to improve the performance of the new order method. We discuss multiple solutions for improving the processes. Finally, we describe how to verify the improvements. Results The results of the delivery time are split up in warehouse and sales products. The warehouse products are stored in the central warehouse and the sales products are ordered at an external supplier and are delivered at the central warehouse, after which they are delivered at the hospital departments immediately. 89% of the warehouse products are delivered within 8 hours after the order moment and 61% of the sales products are delivered within 5 days after the order moment. The main causes of too late delivery are (i) the read out moments of the order boards, (ii) the throughput times of the order process, (iii) the number of employees working on a process, (iv) the route plan, and (v) the delivery time of an external supplier. We conclude the performance for the warehouse products is good, but still can be improved by the logistic department. In our opinion, the performance for the sales products is too low. We conclude that the logistic department cannot guarantee that the department warehouse always has enough stock. The out-of-stock moments are calculated by the number of order cards that are placed on the order board. When both cards of one product are placed on the order board, we assume that the department has an out-of-stock moment. We conclude that in 20% of the moments an order card is placed on the order board, it is the second card. In our view this result is not good. The probability to get an out-of-stock moment seems too high. We make a distinction between different reasons of an out-of-stock moment, namely (i) a wrong bin value, (ii) a suboptimal process, and (iii) a wrong order card procedure. With a wrong order card procedure we mean that the user on the department is not following the correct order procedure, mostly this involves forgetting to place the order card on the order board. With a wrong bin value we mean that the determined stored value of a product in a bin is too low to have enough stock until the next delivery moment. A suboptimal delivery process means that the read out time or delivery moment does not correspond to the consumption on the departments. We find that 38% of these out-of-stock moments is caused by a wrong procedure and 62% is caused by a suboptimal process or a wrong bin value. We conclude that not only the logistics process, but also the ordering process should be improved. The logistic process needs to be improved by the logistic department. The wrong procedure needs to be improved by the department staff. Furthermore, we conclude that most out-of-stock moments caused by a wrong bin value or suboptimal process take place in the weekend or on Monday. We suspect that these out-of-stock moments are caused by the fact that the logistic department is not operational in the weekend. The number of order card and order board errors are calculated by the number of times the order cards and order boards show errors, caused by a too high or too low signal strength in either the cards or the boards. We find 492 order cards that show an error in our three months reference period. We conclude these decrease the system reliability. We notice 2 order boards that may have a low system reliability. In order to improve the delivery time performance of the new order method, we have the following recommendations. We advise the hospital to determine the read out moments based on the start time of the picking process to ensure less delay in delivery time. Furthermore, we advise to determine the time intervals between the read out moment such that they agree with the throughput time of order picking. Since it appears that the delivery timeliness of route orange is much lower in comparison with the other routes, we propose to reschedule route orange. In our view the best solution is to remove the departments with an order board from route orange and include these in route blue, red and white. To decrease the out-of-stock moments we advise the hospital to read out order boards of the nursing and emergency departments and deliver products in the weekend. Furthermore, we advise the hospital to plan a second read out moment on the nursing and emergency department in the afternoon and increase the stock level value of some products. These departments show a high demand of products and the most out-of-stock moments. We also advise to focus on the user procedure. Let the user be aware how the method works, to avoid out-of-stock moments caused by a wrong order procedure. The last improvement we suggest is to improve the signal strength of the order boards that show errors and replace the order cards that decrease the system reliability. This needs to be done by the logistic deparment, which is responsible for the order boards and order cards. Conclusion First, we presume the selected time interval contains enough data to draw a correct conclusion and the results of the KPIs show a clear picture of the performance of the new order method. Overall we conclude, after one year the performance of the new order method is not very good, but not very bad either. We conclude that the processes are carried out correctly because most of the products are delivered within 8 hours and the number of order cards and order boards that show an error is limited and can easily be further reduced. We conclude that the probability of an out-of-stock moment is high. However, we also conclude that the processes can be further optimized with our improvements. We find planning, behaviour and system improvements. We expect that the planning improvements will have the most impact on the performance of the new order method. Furthermore, because the demand of care can vary at different time periods we advise the hospital to analyse the KPIs performance frequently which can be done by the logistic department. The logistic department is responsible for the new order method and has the correct data to analyse the performance. By regularly reassessing the performance the logistic department can respond quickly and adequately to performance changes.
Item Type:Essay (Master)
Faculty:BMS: Behavioural, Management and Social Sciences
Subject:31 mathematics
Programme:Industrial Engineering and Management MSc (60029)
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