Adaptive MCMC methods with applications in environmental and geophysical models

This work presents new, efficient Markov chain Monte Carlo (MCMC) simulation methods for statistical analysis in various modelling applications. When using MCMC methods, the model is simulated repeatedly to explore the probability distribution describing the uncertainties in model parameters and predictions. In adaptive MCMC methods based on the Metropolis-Hastings algorithm, the proposal distribution needed by the algorithm learns from the target distribution as the simulation proceeds. Adaptive MCMC methods have been subject of intensive research lately, as they open a way for essentially easier use of the methodology. The lack of user-friendly computer programs has been a main obstacle for wider acceptance of the methods. This work provides two new adaptive MCMC methods: DRAM and AARJ. The DRAM method has been built especially to work in high dimensional and non-linear problems. The AARJ method is an extension to DRAM for model selection problems, where the mathematical formulation of the model is uncertain and we want simultaneously to fit several different models to the same observations. The methods were developed while keeping in mind the needs of modelling applications typical in environmental sciences. The development work has been pursued while working with several application projects. The applications presented in this work are: a winter time oxygen concentration model for Lake Tuusulanjärvi and adaptive control of the aerator; a nutrition model for Lake Pyhäjärvi and lake management planning; validation of the algorithms of the GOMOS ozone remote sensing instrument on board the Envisat satellite of European Space Agency and the study of the effects of aerosol model selection on the GOMOS algorithm.

Cost efficient supply processes for the Compact Slim Elevator Door

The aim of this thesis was to observe possibilities to enhance the development of manufacturing costs savings and competitiveness related to the compact KONE Renova Slim elevator door. Compact slim doors are especially designed for EMEA markets. EMEA market area is characterized by highly competitive pricing and lead times which are manifested as pressures to decrease manufacturing costs and lead times of the compact elevator door. The new elevator safety code EN81-20 coming live during the spring 2016 will also have a negative impact on the cost and competitiveness development making the situation more acute. As a sheet metal product the KONE Renova slim is highly variable. Manufacturing methods utilized in the production are common and robust methods. Due to the low volumes, high variability and tight lead times the manufacturing of the doors is facing difficulties. Manufacturing of the doors is outsourced to two individual suppliers Stera and Wittur. This thesis was implemented in collaboration with Stera. KONE and Stera pursue a long term and close partnership where the benefits reached by the collaboration are shared equally. Despite the aims, the collaboration between companies is not totally visible and various barriers are hampering the development towards more efficient ways of working. Based on the empirical studies related to this thesis, an efficient standardized (A+) process was developed for the main variations of the compact elevator door. Using the standardized process KONE is able to order the most important AMDS door variations from Stera with increased quality, lower manufacturing costs and manufacturing lead time compared to the current situation. In addition to all the benefits, the standardized (A+) process also includes risks in practice. KONE and the door supplier need to consider these practical risks together before decisions are made.

Increasing value add in white collar work using lean methods

The efficient indirect office work brings competitive advantage for companies in a rapidly changing business environment. The direct work methods in factory floors have been developed already for decades, but the office work is an area where the potential to improve the value add has not been studied and utilized systematically so far. The first objective of the thesis work is to find useful method for identifying and managing value add using literature. The usefulness of the method is validated in the case company`s environment. The second objective of the work is to understand what kind of effort is required to create more efficient target setting for the white collar employees. The operative level targets should be linked more tightly to the company strategy. Lean methods are selected as a tool for the improvement, since they are widely used in all kinds of industries and they are already familiar in other functions in the case company. Based on the literature review, suitable improvement methods are selected. The core of the lean is to identify the value add of a customer and eliminate the waste. Also visual control, cross functional work team, flow office and continuous improvement are used. The methods are tested in one production line and the results and feedback indicate that methods are useful in the studied environment.