University of Twente Student Theses


Automating and improving the printing planning process: Jongbloed BV

Colijn, A. (2013) Automating and improving the printing planning process: Jongbloed BV.

[img] PDF
Abstract:Jongbloed is a company that is known for its ability to manufacture books on very thin paper. Nowadays, it consists of two business units namely a publishing and a book manufacturing unit. The book manufacturing business unit uses an almost manual production planning which is labour-intensive. Jongbloed would like to purchase a production planning software package, such that the production planning can be automated and improved. However, there is a wide variety of production planning rules that can be used in various production planning packages. Therefore, we were asked to analyse these rules and select the best performing rule given several performance indicators. After studying the current situation, we formulated the following main research question: “What production planning rules should be used to automate and improve Jongbloed’s production planning?” First, we analyse the current situation. We want to know the magnitude of improvement of a new production planning software package, and we therefore need to quantitatively describe the current situation. We compute that in approximately 62 percent of the leadtime, a project is waiting for either materials or the next process. Obviously, zero waiting time is impossible because machines fail and need maintenance, suppliers do not deliver raw materials and other projects also need to be processed. All these reasons cause waiting time. Still, the improvement potential is quite large. Literature provides us with several methods to automate and improve the production planning. Roughly speaking, there are two methods of ‘simple’ production planning namely global and local. A local production planning is a production planning per machine, whereas a global production planning is an overall planning for the complete factory. However, not a single method outperforms all the others. Therefore, we build a computer model that has the same characteristics as the production process of Jongbloed. It allows us to analyse different production planning rules, without actually implementing them. After running the computer model with the different types of production planning, we conclude that local methods outperform global production planning approaches. Global production planning methods do not automatically reschedule, whereas local production planning are able to do so. There is one major drawback of local production planning. As the planning is per machine and only includes projects that are present in the queue (and thus not future projects), its horizon is very short. Therefore, it is impossible to react to future spikes in the number of waiting projects and plan preventive maintenance. So, we would like to implement the best performing global production planning rule namely global forward planning. This rule makes a complete planning for the factory and adds the projects to all the necessary processes, at the first possible time slot. If we compare the global forward planning method to the current situation, given the four performance indicators Work In Progress (WIP), lead time, tardiness, and percentage projects tardy, it gives an overall improvement of 22 percent. Especially the WIP performance increases, the performance on the other three performance indicators remains stable. Therefore, we would like to advise the global forward planning method to improve and automate Jongbloed’s production planning.
Item Type:Essay (Master)
Jongbloed BV, the Netherlands
Faculty:BMS: Behavioural, Management and Social Sciences
Subject:85 business administration, organizational science
Programme:Industrial Engineering and Management MSc (60029)
Link to this item:
Export this item as:BibTeX
HTML Citation
Reference Manager


Repository Staff Only: item control page