PhD defense Jan Claes

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Lately, the focus of organizations is changing fundamentally. Where they used to spend almost exclusively attention to results, in terms of goods, services, revenue and costs, they are now concerned about the efficiency of their business processes. Each step of the business processes needs to be known, controlled and optimized. This explains the huge effort that many organizations currently put into the mapping of their processes in so-called (business) process models.

Unfortunately, sometimes these models do not (completely) reflect the business reality or the reader of the model does not interpret the represented information as intended. Hence, whereas on the one hand we observe how organizations are attaching increasing importance to these models, on the other hand we notice how the quality of process models in companies often proves to be insufficient.

The doctoral research makes a significant contribution in this context. This work investigates in detail how people create process models and why and when this goes wrong. A better understanding of current process modeling practice will form the basis for the development of concrete guidelines that result in the construction of better process models in the future.  The first study investigated how we can represent the approach of different modelers in a cognitive effective way, in order to facilitate knowledge building. For this purpose the PPMChart was developed. It represents the different operations of a modeler in a modeling tool in such a way that patterns in their way of working can be detected easily. Through the collection of 704 unique modeling executions (a joint contribution of several authors in the research domain), and through the development of a concrete implementation of the visualization, it became possible to gather a great amount of insights about how different people work in different situations while modeling a concrete process.

The second study explored, based on the discovered modeling patterns of the first study, the potential relations between how process models were being constructed and which quality was delivered. To be precise, three modeling patterns from the previous study were investigated further in their relation with the understandability of the produced process model. By comparing the PPMCharts that show these patterns with corresponding process models, a connection was found in each case. It was noticed that when a process model was constructed in consecutive blocks (i.e., in a structured way), a better understandable process model was produced. A second relation stated that modelers who (frequently) moved (many) model elements during modeling usually created a less understandable model. The third connection was found between the amount of time spent at constructing the model and a declining understandability of the resulting model. These relations were established graphically on paper, but were also confirmed by a simple statistical analysis.

The third study selected one of the relations from the previous study, i.e., the relation between structured modeling and model quality, and investigated this relation in more detail. Again, the PPMChart was used, which has lead to the identification of different ways of structured process modeling. When a task is difficult, people will spontaneously split up this task in sub-tasks that are executed consecutively (instead of simultaneously). Structuring is the way in which the splitting of tasks is handled. It was found that when this happens consistently and according to certain logic, modeling became more effective and more efficient. Effective because a process model was created with less syntactic and semantic errors and efficient because it took less time and modeling operations. Still, we noticed that splitting up the modeling in sub-tasks in a structured way, did not always lead to a positive result. This can be explained by some people structuring the modeling in the wrong way. Our brain has cognitive preferences that cause certain ways of working not to fit. The study identified three important cognitive preferences: does one have a sequential or a global learning style, how context-dependent one is and how big one”s desire and need for structure is. The Structured Process Modeling Theory was developed, which captures these relations and which can form the basis for the development of an optimal individual approach to process modeling. In our opinion the theory has the potential to also be applicable in a broader context and to help solving various types of problems effectively and efficiently.

Project: Performance measurements in the semi-process industry

The Information Systems group is often contacted by industrial organizations with assignments that could lead to student projects at various levels (master thesis project, bachelor completion project, etc.) Through this website we make these topics available to our students. In this post, we announce one such project, involving company Marel.

Performance measurements in the semi-process industry

The organization

Marel is an international supplier of advanced systems for the food processing industry. With around 3700 employees worldwide, Marel focuses on the segments of Poultry Processing, Further Processing, Meat and Fish. At its modern plant in Boxmeer, the operating company Marel Stork Poultry Processing B.V. focuses on the design, production and installation of production systems for the poultry processing industry. As the world market leader, the organization is constantly looking for opportunities to increase the productivity of its customers, within the bounds of quality and innovation. In addition to offices in Boxmeer (NL), Dongen (NL) and Gainesville (Georgia, USA), the organization has regional offices in a large number of countries.

Master Thesis assignment

The highly automated production lines of modern poultry processors process 13.500 broilers per hour. Each broiler has its own quality specifications and unique weight, which determines its destination and potential value. The destination of a broiler can end up in several different articles; a modern retail plant offers a variety of more than 500 product articles.  In order to make optimal use of the potential value of each individual broiler an information system is required. A lot of attention is paid to animal welfare, food safety, quality, full traceability, water and energy consumption. The aim is to add value to poultry as effectively as possible. The overall performance of a poultry processor is depending on a lot of factors, one of the indirect factors is production planning. Production planning on a daily level is a real challenge in the poultry processing industry. The uncertainty of the demand on one side and the dynamics of the raw material supply on the other side ask for planning skills of the processor. A lot of data and an information system are used to control the production. The exact impact of planning and scheduling is difficult to determine, but enhancements of the planning performance gains big advantages. Innova is the provided information system by Marel to support planners. For now we have an interesting Master Thesis assignment for an entrepreneurial student. In order to improve the planning performance on the long term, initially the performance should be measured in order to quantify possible improvements. The assignment is to set up a method to measure the production planning performance of a retail poultry processor. The business process of production planning is known and can be used as a starting point. Determining (key) performance indicators and an overview of required vs. redundant (available) data are the most obvious deliverables.

Contact information: Marel, via Rik Eshuis, or Irene Vanderfeesten.