Universiẗat, Diss., 1998--Bremen.

Universiẗat, Diss., 2006--Paderborn.

Mellan 1990 och 2016 ökade de vägburna godstransporterna med cirka 50 procent och spås fortsätta öka ännu mer till år 2030. Fokus har tidigare legat på kostnadsminimering men har nu skiftat till att effektivisera transporterna. En förutsättning för att kunna effektivisera är att mäta och följa upp transporter, något som bland annat digitala verktyg möjliggör. En bransch som är i behov av effektivisering av transporter är anläggningsbranschen, bland annat på grund av låg innovationsgrad samt minskad lönsamhet hos de stora aktörerna. Syftet med denna studie är således att undersöka hur en entreprenör inom anläggningsbranschen kan definiera en effektivt utnyttjad anläggningstransport samt att ta fram prestationsmått för att mäta utnyttjandegraden av dessa. Studien har genomförts som en fallstudie på Skanska Sverige AB vid enheten Skanska Inköp. Studerade transportflöden är transport av asfalt från ett asfaltverk till ett läggarlag samt transport av schaktmassor från ett projekt till en deponi. Första steget i studien var att identifiera definitioner inom fallföretaget på vad en effektivt utnyttjad anläggningstransport är. Detta gjordes genom intervjuer, observationer, benchmarking samt en workshop. Därefter jämfördes definitionerna med litteratur på hur utnyttjandegrad kan definieras för transporter. Avslutningsvis anordnades en workshop där utvalda personer från fallföretaget diskuterade fram lämpade prestationsmått på utnyttjandegrad, med syftet att förbättra utnyttjandet. En specifik definition av en effektivt utnyttjad anläggningstransport inom fallföretaget framkom inte. Istället identifierades13 olika definitioner som inkluderar allt från engagerade chaufförer till att fordonet alltid är i rörelse. De definitioner som berörde förbättringsområden inom fallföretaget bröts ned ytterligarei prestationsmått för att mäta utnyttjandegrad, där utnyttjandegrad är förhållandet mellan output och kapacitet hos en resurs eller aktivitet. Prestationsmåtten delades in i dimensionerna kvalitet, tid, produktivitet och finansiellt. Kvalitet syftar till hur väl en specifik uppgift genomförs, tid identifierar aktiviteter där tid kan sparas, produktivitet till hur väl en specifik resurs används och finansiellt identifierar kostsamma aktiviteter i processen. Det är fördelaktigt att mäta inom alla fyra dimensioner för att skapa ett holistiskt perspektiv. Fallföretaget rekommenderas därmed att börja mäta följande fyra prestationsmått för utnyttjandegrad, vilka presenteras i tabellen nedan. <img 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

Det här är en kadidatsuppsatsinom industriell logistik som handlar om Industri 4.0 inom distributionskedjor i Norrbotten. Industri 4.0 har under den senaste tiden varit ett populärt ämne med ett växande antal publicerade artiklar och allt fler verksamheter har visat ett allt större intresse. Med rapporten vill vi fördjupa vår kunskap inom Industri 4.0, få en bättre förståelse för Industri 4.0s påverkan på distributionskedjor samt undersöka verksamheters insikt i ämnet. Undersökningen har utgått från tre huvudfrågor: 1) Vilka möjligheter och risker skapar Industri 4.0 för distributionskedjan? 2) Används Industri 4.0 i distributionskedjor i Norrbotten? Om inte, varför inte? 3) Finns det planer för att implementera Industri 4.0 i distributionskedjor i Norrbotten? Data har samlats in från tio relevanta artiklar, fem intervjuer med logistikchefer på några av regionens största verksamheter och tre så kallade kompetensintervjuer med personer som har insikt i Industri 4.0 inom regionen. Resultaten visar att möjligheterna överväger riskerna. Exempel på möjligheter är flexibilitet, en mer integrerad distributionskedja, kostnadseffektivitet, effektivare i distributionskedjan, mer hållbart, förbättrad transporttid och tillgång till realtidsdata. Exempel på risker är datasäkerhet, brist på standard för systemen, integritetskränkande, sämre arbetsmönster, komplexitet, den lagliga aspekten och ”high cost investment” med mera. Idag används inte Industri 4.0 i distributionskedjan i Norrbotten. Däremot finns det delar av tekniken som används. Det sker en kontinuerlig utveckling av tekniken i verksamheters distributionskedjor men det är svårt att konkret säga inom vilken tidsram Industri 4.0 kommer att vara implementerat i verksamheters distributionskedjor. Undersökningen kommer fram till att det kommer att krävas en ändring av verksamheter i Norrbottens distributionskedjor med hjälp av nya innovativa tekniker. Den här rapporten kan inte säkerhetsställainom vilken tidsram Industri 4.0 kommer bli aktivt inom distributionskedjori regionen.

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På dagens hårt konkurantutsatta marknader tvingas företag hitta nya sätt för att kunna tillhandahålla ett större produktsortiment och samtidigt kunna förse sina kunder med produkter på kortare ledtid. För att kunna åstadkomma detta blir det allt vanligare att företag idag styr sin produktion utifrån en assemble-to-order-strategi (ATO). När antalet slutprodukter som framställs utifrån den här tillverkningsstrategin ökar, i syfte att erbjuda dessa på kortare ledtid, krävs det ofta att ett större antal nya komponenter måste lagerhållas samt att kvantiteten av befintligt lagerhållna komponenter måste utökas. Kostnaderna för företaget kommer således att öka, i form av ökad kapitalbindning, som ett resultat av att antal produkter i arbete ökar. Denna uppsatts behandlar en fallstudie som utförts på Bosch Rexroth Mellansel AB, som är en ledande leverantör av stora hydrauliska drivlösningar och som framställer flertalet av sina produkter utifrån en ATO-strategi. Företaget saknar idag ett tillvägagångssätt för att ta reda på vilka ekonomiska konsekvenser som deras lagerhållning av komponenter medför när ytterligare hydraulmotorer erbjuds på kortare ledtid. Utifrån detta, samt det faktum att förädlingsvärdet för deras interntillverkade komponenter är betydligt högre än värdet för deras inköpsartiklar, är syftet med denna studie att undersöka hur Bosch Rexroth Mellansel kan estimera den förändrade lagerhållningskostnaden som uppstår för färdigbearbetade interntillverkade komponenter när fler hydraulmotorer erbjuds på kortare ledtid. Studien genomfördes utifrån en kvantitativ forskningsmetod där data samlades in från fallföretagets affärssystem SAP. Den sammanställda data har i denna studie analyserats utifrån Microsoft Excel och programspråket Python. Baserat på studerad litteratur inom området, empiri och analys har studien resulterat i en metodik som omfattar fyra steg som Bosch Rexroth Mellansel rekommenderas att använda för att estimera den förändrade lagerhållningskostnaden som uppstår när fler hydraulmotorer erbjuds på kortare ledtid. Till följd av hur Bosch Rexroth Mellansel beräknar sina lagernivåer framgick det tydligt att det enbart är en hydraulmotors ingående interntillverkade komponenter som inte lagerhålls som kan komma att ha en inverkan på den förändrade lagerhållningskostnaden, när denna ska erbjudas på kortare ledtid.

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The content of this thesis is safety and mobility of children crossing streets as pedestrians and bicyclists. The risk of fatal injury is higher for pedestrians and bicyclists, especially for children and elderly, than for other road users except motorcyclists. The effect of speed reducing devices installed to increase the safety of pedestrians and bicyclists at marked pedestrian crosswalks are studied and evaluated in before-and-after studies. Design principles of a safe environment for children as pedestrians and bicyclists are suggested based on research in this thesis and on earlier research results. Most important is that actual motor vehicle speeds are no more than 30 km/h, wherever children (regularly) cross streets. / Godkänd; 2004; 20061026 (haneit)

Partnership is about developing good business relations between two or more companies. It is a simple and effective working method that can be applied in many situations, including developing new products and associated tooling which is the focus of this thesis. The goal with partnership is not to have a cosy relationship between the partners; but rather as an effective way to make money using a simple working method. The work presented in this thesis is the result of a joint project between Luleå University of Technology and the Pressoform consortium. Pressoform was interested in applying the results in the tooling industry in Sweden and therefore funded the research. The aim of the work behind this thesis was to show that by implementing an effective working method, based on partnership, product development lead-times could be reduced without reduction in quality or increased costs. The specific domain of the work was the development process for form tools such as tools for injection moulding, die casting and sheet metal forming. The advantages with working in a partnership include the possibility to achieve a reduced lead-time and at the same time increase quality and reduce the cost by using an effective working method for developing new products. There are however risks with partnerships, it is a more expensive relationship to maintain, customers are more tightly bounded to suppliers. Another risk could be that the customers by tradition have looked for a power relationship, where they control the form of the relationship. On the other hand a partnership may result in customers and suppliers becoming too close and loose the business like attitude. Partnership is a long-term investment and a strategy for the companies involved to make more money in the long term. Personal relations and trust are important in a long-term strategy, since the companies expect to work together for a long period of time. Partnership should therefore only be conducted with companies that are trusted. In addition effective methods should be applied to speed up the development process for the product and tooling. The business process should be conducted without the traditional quotation process, since this is both time- and cost consuming. Instead of using quotes, buying tools on a cost plus basis is far more effective. The product development work must be conducted with active input from all the three parties. It should be conducted in teams to improve communication, the manufacturer and the tool manufacturer being involved in the team to give input in their expertise areas. Using 3D CAD software has been shown to reduce development lead times by 50% compared to using 2D CAD software. Of the five cases followed, a reduction in lead-time was found in three of them. In one case the project failed due to manufacturing problems whilst the last case focused on the effective product development process in general. / Godkänd; 2002; 20070222 (ysko)

This licentiate thesis deals with traffic safety of pedestrians and cyclists, especially children, in urban areas. The aim is to develop a method based on video recordings to describe road safety and mobility for pedestrians and cyclists, especially children, at intersections in urban areas. It is tested using empirical data from intersections in Borås, Sweden. The amount of incidents and conflicts between vehicles and pedestrians and cyclists are lower for all age groups after reconstruction. Before reconstructions the share of car drivers giving way were low independent of the pedestrians age. The design of an intersection influences the different road users’ behaviour. At intersections where more pedestrians walk on the marked zebra crossing the children are benefited the most. / <p>Godkänd; 2001; 20061101 (ysko)</p>