Logistiikan tarkkuuden ja tehokkuuden kehittäminen. Case: ABB Oy, Motors & Generators, Vaasa

Tämä tutkielma tehdään toimeksiantona ABB Oy:n, Motors & Generators - liiketoimintayksikön Vaasan sähkömoottoritehtaalle. Tutkielman tavoitteena on MM- rakennuksen logistiikan tarkkuuden ja tehokkuuden kehittäminen. Käytännössä tavoite tarkoittaa virheettömyyden lisäämistä materiaalien sijainti- ja tilatiedoissa, varastosaldoissa, sekä ei-jalostavan työn vähentämistä. Työssä keskitytään sähkömoottoritehtaan tuleviin ja sisäisiin materiaali- ja tietovirtoihin logistiikan osalta. Tutkielman teoriaosuudessa tarkastellaan varastonhallinnan periaatteita, varastotoimintaa ja kustannuksia sekä perehdytään varastosaldojen epätarkkuuteen. Empiirinen tutkimus suoritetaan tapaustutkimuksena, pistokokeina. 14.-28.2.2014 välisenä aikana tehtyjen pistokokeiden perusteella, kun tietojärjestelmässä olevaa ja fyysistä varastosaldoa verrataan, saadaan tuloksista selvitettyä varastosaldojen nykytila. Työssä myös analysoidaan inventointiraportteja, joiden tiedot ajoittuvat 2012-2013 vuosille. Tuotantotyöntekijöille tehdään kysely rakennevirheistä ja osien ristiinkäytöstä. Kyselyn perusteella voidaan havainnoida, kuinka usein ja missä tuoteryhmissä virheitä esiintyy. Logistiikan tehokkuuden kehittämistä käsitellään Kaizen -työpajassa. Kaizen -työpajan avulla saadaan uusia ideoita ja keinoja, joilla logistiikan tehokkuutta voidaan parantaa. Tutkimusten perusteella pystyttiin tunnistamaan varastosaldovirheiden esiintymisprosentit ja varastosaldovirheiden syntymisen syyt sekä logistiikan tehokkuutta haittaavat epäkohdat. Tutkimustulosten analyysien avulla voitiin esittää konkreettisia kehitysehdotuksia, kuten resurssien tehokkaampaa käyttöä, työntekijöiden sitouttamista ja kouluttamista sekä ylituotannon vähentämista, joiden avulla logistiikan tarkkuus ja tehokkuus paranee. Työssä myös tuotiin esiin kustannuksia, jotka syntyvät varasaldojen epätarkkuuden vaikutuksista.fi=Opinnäytetyö kokotekstinä PDF-muodossa.|en=Thesis fulltext in PDF format.|sv=Lärdomsprov tillgängligt som fulltext i PDF-format

Dissecting the polygenic basis of atherosclerosis via disease-associated cell state signatures

Coronary artery disease (CAD) is a pandemic disease where up to half of the risk is explained by genetic factors. Advanced insights into the genetic basis of CAD require deeper understanding of the contributions of different cell types, molecular pathways, and genes to disease heritability. Here, we investigate the biological diversity of atherosclerosis-associated cell states and interrogate their contribution to the genetic risk of CAD by using single-cell and bulk RNA sequencing (RNA-seq) of mouse and human lesions. We identified 12 disease-associated cell states that we characterized further by gene set functional profiling, ligand-receptor prediction, and transcription factor inference. Importantly, Vcam1+ smooth muscle cell state genes contributed most to SNP-based heritability of CAD. In line with this, genetic variants near smooth muscle cell state genes and regulatory elements explained the largest fraction of CAD-risk variance between individuals. Using this information for variant prioritization, we derived a hybrid polygenic risk score (PRS) that demonstrated improved performance over a classical PRS. Our results provide insights into the biological mechanisms associated with CAD risk, which could make a promising contribution to precision medicine and tailored therapeutic interventions in the future.publishedVersionPeer reviewe

Nondestructive Evaluation of Mechanical and Histological Properties of the Human Aorta With Near-Infrared Spectroscopy

Introduction: Ascending aortic dilatation is a well-known risk factor for aortic rupture. Indications for aortic replacement in its dilatation concomitant to other open-heart surgery exist; however, cut-off values based solely on aortic diameter may fail to identify patients with weakened aortic tissue. We introduce near-infrared spectroscopy (NIRS) as a diagnostic tool to nondestructively evaluate the structural and compositional properties of the human ascending aorta during open-heart surgeries. During open-heart surgery, NIRS could provide information regarding tissue viability in situ and thus contribute to the decision of optimal surgical repair. Materials and methods: Samples were collected from patients with ascending aortic aneurysm (n = 23) undergoing elective aortic reconstruction surgery and from healthy subjects (n = 4). The samples were subjected to spectroscopic measurements, biomechanical testing, and histological analysis. The relationship between the near-infrared spectra and biomechanical and histological properties was investigated by adapting partial least squares regression. Results: Moderate prediction performance was achieved with biomechanical properties (r = 0.681, normalized root-mean-square error of cross-validation = 17.9%) and histological properties (r = 0.602, normalized root-mean-square error of cross-validation = 22.2%). Especially the performance with parameters describing the aorta's ultimate strength, for example, failure strain (r = 0.658), and elasticity (phase difference, r = 0.875) were promising and could, therefore, provide quantitative information on the rupture sensitivity of the aorta. For the estimation of histological properties, the results with α-smooth muscle actin (r = 0.581), elastin density (r = 0.973), mucoid extracellular matrix accumulation(r = 0.708), and media thickness (r = 0.866) were promising. Conclusions: NIRS could be a potential technique for in situ evaluation of biomechanical and histological properties of human aorta and therefore useful in patient-specific treatment planning.Peer reviewe

Wall Shear Stress Predicts Media Degeneration and Biomechanical Changes in Thoracic Aorta

Objectives: In thoracic aortic aneurysm (TAA) of the ascending aorta (AA), AA is progressively dilating due to the weakening of the aortic wall. Predicting and preventing aortic dissections and ruptures in TAA continues to be challenging, and more accurate assessment of the AA dilatation, identification of high-risk patients, and timing of repair surgery are required. We investigated whether wall shear stress (WSS) predicts pathological and biomechanical changes in the aortic wall in TAA. Methods: The study included 12 patients with bicuspid (BAV) and 20 patients with the tricuspid aortic valve (TAV). 4D flow magnetic resonance imaging (MRI) was performed a day before aortic replacement surgery. Biomechanical and histological parameters, including assessing of wall strength, media degeneration, elastin, and cell content were analyzed from the resected AA samples. Results: WSSs were greater in the outer curves of the AA compared to the inner curves in all TAA patients. WSSs correlated with media degeneration of the aortic wall (ρ = -0.48, p < 0.01), elastin content (ρ = 0.47, p < 0.01), and aortic wall strength (ρ = -0.49, p = 0.029). Subsequently, the media of the outer curves was thinner, more rigid, and tolerated lower failure strains. Failure values were shown to correlate with smooth muscle cell (SMC) density (ρ = -0.45, p < 0.02), and indicated the more MYH10+ SMCs the lower the strength of the aortic wall structure. More macrophages were detected in patients with severe media degeneration and the areas with lower WSSs. Conclusion: The findings indicate that MRI-derived WSS predicts pathological and biomechanical changes in the aortic wall in patients with TAA and could be used for identification of high-risk patients.publishedVersionPeer reviewe

Wall shear stress predicts media degeneration and biomechanical changes in thoracic aorta

Abstract Objectives: In thoracic aortic aneurysm (TAA) of the ascending aorta (AA), AA is progressively dilating due to the weakening of the aortic wall. Predicting and preventing aortic dissections and ruptures in TAA continues to be challenging, and more accurate assessment of the AA dilatation, identification of high-risk patients, and timing of repair surgery are required. We investigated whether wall shear stress (WSS) predicts pathological and biomechanical changes in the aortic wall in TAA. Methods: The study included 12 patients with bicuspid (BAV) and 20 patients with the tricuspid aortic valve (TAV). 4D flow magnetic resonance imaging (MRI) was performed a day before aortic replacement surgery. Biomechanical and histological parameters, including assessing of wall strength, media degeneration, elastin, and cell content were analyzed from the resected AA samples. Results: WSSs were greater in the outer curves of the AA compared to the inner curves in all TAA patients. WSSs correlated with media degeneration of the aortic wall (ρ = -0.48, ρ &lt; 0.01), elastin content (ρ = 0.47, ρ &lt; 0.01), and aortic wall strength (ρ = -0.49, ρ = 0.029). Subsequently, the media of the outer curves was thinner, more rigid, and tolerated lower failure strains. Failure values were shown to correlate with smooth muscle cell (SMC) density (ρ = -0.45, ρ &lt; 0.02), and indicated the more MYH10⁺ SMCs the lower the strength of the aortic wall structure. More macrophages were detected in patients with severe media degeneration and the areas with lower WSSs. Conclusion: The findings indicate that MRI-derived WSS predicts pathological and biomechanical changes in the aortic wall in patients with TAA and could be used for identification of high-risk patients