Kalman Filtering in Online Paper Quality Assessment

Controlling the quality variables (such as basis weight, moisture etc.) is a vital part of making top quality paper or board. In this thesis, an advanced data assimilation tool is applied to the quality control system (QCS) of a paper or board machine. The functionality of the QCS is based on quality observations that are measured with a traversing scanner making a zigzag path. The basic idea is the following: The measured quality variable has to be separated into its machine direction (MD) and cross direction (CD) variations due to the fact that the QCS works separately in MD and CD. Traditionally this is done simply by assuming one scan of the zigzag path to be the CD profile and its mean value to be one point of the MD trend. In this thesis, a more advanced method is introduced. The fundamental idea is to use the signals’ frequency components to represent the variation in both CD and MD. To be able to get to the frequency domain, the Fourier transform is utilized. The frequency domain, that is, the Fourier components are then used as a state vector in a Kalman filter. The Kalman filter is a widely used data assimilation tool to combine noisy observations with a model. The observations here refer to the quality measurements and the model to the Fourier frequency components. By implementing the two dimensional Fourier transform into the Kalman filter, we get an advanced tool for the separation of CD and MD components in total variation or, to be more general, for data assimilation. A piece of a paper roll is analyzed and this tool is applied to model the dataset. As a result, it is clear that the Kalman filter algorithm is able to reconstruct the main features of the dataset from a zigzag path. Although the results are made with a very short sample of paper roll, it seems that this method has great potential to be used later on as a part of the quality control system.

Simulating the performance of paper machine control

The topic of this thesis is the simulation of a combination of several control and data assimilation methods, meant to be used for controlling the quality of paper in a paper machine. Paper making is a very complex process and the information obtained from the web is sparse. A paper web scanner can only measure a zig zag path on the web. An assimilation method is needed to process estimates for Machine Direction (MD) and Cross Direction (CD) profiles of the web. Quality control is based on these measurements. There is an increasing need for intelligent methods to assist in data assimilation. The target of this thesis is to study how such intelligent assimilation methods are affecting paper web quality. This work is based on a paper web simulator, which has been developed in the TEKES funded MASI NoTes project. The simulator is a valuable tool in comparing different assimilation methods. The thesis contains the comparison of four different assimilation methods. These data assimilation methods are a first order Bayesian model estimator, an ARMA model based on a higher order Bayesian estimator, a Fourier transform based Kalman filter estimator and a simple block estimator. The last one can be considered to be close to current operational methods. From these methods Bayesian, ARMA and Kalman all seem to have advantages over the commercial one. The Kalman and ARMA estimators seems to be best in overall performance.

Enhancing absorptive capacity in a non-research and development. An action research approach to converting individual observations into organisational awareness

The ability to recognize potential knowledge and convert it into business opportunities is one of the key factors of renewal in uncertain environments. This thesis examines absorptive capacity in the context of non-research and development innovation, with a primary focus on the social interaction that facilitates the absorption of knowledge. It proposes that everyone is and should be entitled to take part in the social interaction that shapes individual observations into innovations. Both innovation and absorptive capacity have been traditionally related to research and development departments and institutions. These innovations need to be adopted and adapted by others. This so-called waterfall model of innovations is only one aspect of new knowledge generation and innovation. In addition to this Science–Technology–Innovation perspective, more attention has been recently paid to the Doing–Using–Interacting mode of generating new knowledge and innovations. The amount of literature on absorptive capacity is vast, yet the concept is reified. The greater part of the literature links absorptive capacity to research and development departments. Some publications have focused on the nature of absorptive capacity in practice and the role of social interaction in enhancing it. Recent literature on absorptive capacity calls for studies that shed light on the relationship between individual absorptive capacity and organisational absorptive capacity. There has also been a call to examine absorptive capacity in non-research and development environments. Drawing on the literature on employee-driven innovation and social capital, this thesis looks at how individual observations and ideas are converted into something that an organisation can use. The critical phases of absorptive capacity, during which the ideas of individuals are incorporated into a group context, are assimilation and transformation. These two phases are seen as complementary: whereas assimilation is the application of easy-to-accept knowledge, transformation challenges the current way of thinking. The two require distinct kinds of social interaction and practices. The results of this study can been crystallised thus: “Enhancing absorptive capacity in practicebased non-research and development context is to organise the optimal circumstances for social interaction. Every individual is a potential source of signals leading to innovations. The individual, thus, recognises opportunities and acquires signals. Through the social interaction processes of assimilation and transformation, these signals are processed into the organisation’s reality and language. The conditions of creative social capital facilitate the interplay between assimilation and transformation. An organisation that strives for employee-driven innovation gains the benefits of a broader surface for opportunity recognition and faster absorption.” If organisations and managers become more aware of the benefits of enhancing absorptive capacity in practice, they have reason to assign resources to those practices that facilitate the creation of absorptive capacity. By recognising the underlying social mechanisms and structural features that lead either to assimilation or transformation, it is easier to balance between renewal and effective operations.