Purpose – The study aimed to investigate long-term organizational planning in a smart warehouse environment with unpredictable demand to understand how these organizations are able to make sustainable decisions from a social and economic perspective.   Methodology – To fulfil the purpose of the study, a single case study was conducted which included six interviews and two observations at the case company. The interviews were conducted to increase the understanding of organizational planning in unpredictable environments whereas the observations were conducted to increase the understanding of smart warehouses. The empirical data was interpreted and analyzed through thematic data analysis and triangulation in order to identify patterns in the collected data.  Findings – Ten sustainable decisions were identified from theory and empirical data, of which five decisions regarding social sustainability and five decisions regarding economic sustainability. These decisions can be used as a guide for organizations operating in smart warehouses to promote sustainable long-term organizational planning.   Implications – The study’s theoretical contributions refer to an insight of how smart e-commerce warehouses are influenced by unpredictable demand and the impact on the daily operations. Furthermore, the study provides an increased understanding of RCSR systems.  The practical contributions refer to the ten sustainable decisions which can promote strategic decision-making for sustainable long-term organizational planning. Moreover, the study contributes to the insight of what competencies are needed within Industry 4.0 and Industry 5.0 organizations and how to these competencies can be promoted.  Limitations – If a multiple-case study would have been conducted it is possible that further perspectives of the sustainable decisions would have been detected. It is also possible if more employees would have been participated in the interviews that other perspectives would have been achieved.

The logistics industry is one of the most important industries, being an important component of a company's activities. In recent years, the industry has gone through a large number of changes. These had the purpose of making the processes more efficient in order to reduce costs or to increase the degree of competitiveness. A very important process in the logistics industry is the allocation of roles in warehouses. Not using the available resources to their maximum capacity leads to an increase in the processing time of the units as well as to a decrease in the profitability of the companies. Allocation is done manually in the warehouse, being a complex task in which many constraints and variations must be taken into account. AI technologies and IoT systems have the potential to simplify the process of assigning workers. For this research, a warehouse in Germany operated by the Amazon company was studied. In addition to the benefits that this transition can have from a social point of view, helping to equalize the roles of high complexity and the appropriate rotation of jobs to ensure equal opportunities for development, there is an opportunity to reduce the costs associated with this process by up to 90%. This last aspect is dependent on the degree of modernization of the warehouse and on the way in which the role allocation process is carried out at the time. Most of the IoT systems necessary for the digitization and automation of this process are already implemented in warehouses. However, a common architecture is needed to be able to guarantee the integration and compatibility of the systems. The main blocker in this transition remains public opinion and financial factors, companies with a large volume of units potentially benefiting from economies of scale. / Logistikbranschen är en av de viktigaste branscherna och är en viktig del av ett företags verksamhet. De senaste åren har branschen genomgått ett stort antal förändringar. Dessa hade till syfte att effektivisera processerna för att minska kostnaderna eller öka graden av konkurrenskraft. En mycket viktig process inom logistikbranschen är fördelningen av roller i lager. Att inte använda de tillgängliga resurserna till sin maximala kapacitet leder till en ökad handläggningstid för enheterna samt till en minskad lönsamhet för företagen. Allokering sker manuellt i lagret, vilket är en komplex uppgift där många begränsningar och variationer måste beaktas. AI-teknik och IoT-system har potential att förenkla processen för att tilldela arbetare. För denna forskning studerades ett lager i Tyskland som drivs av Amazon-företaget. Förutom de fördelar som denna övergång kan ha ur en social synvinkel, hjälpa till att utjämna rollerna med hög komplexitet och lämplig rotation av jobb för att säkerställa lika möjligheter till utveckling, finns det en möjlighet att minska kostnaderna förknippade med denna process med upp till 90 %. Den sista aspekten är beroende av graden av modernisering av lagret och på det sätt på vilket rollfördelning processen går till vid tillfället. De flesta av de IoT-system som krävs för digitalisering och automatisering av denna process är redan implementerade i lager. Det behövs dock en gemensam arkitektur för att kunna garantera systemets integration och kompatibilitet. Den huvudsakliga blockeraren i denna övergång är fortfarande den allmänna opinionen och finansiella faktorer, företag med en stor volym av enheter som potentiellt kan dra nytta av stordriftsfördelar.

Introduktion: Digital teknik förändrar arbetslivets processer och kan påverka arbetstagarnas arbetsmiljö. Europakommissionens strategi, Industri 5.0, uppmanar till ett människocentrerat förhållningssätt som bidrar till välbefinnande och hållbarhet i den digitala utvecklingen. Syfte: Syftet var att analysera synen på arbetarnas hälsa och välbefinnande i studier som åberopar Europakommissionens strategi Industri 5.0. Forskningsfrågorna letade svar på hur välbefinnande beskrivs, om forskningen anlägger ett teknik- eller människocentrerat perspektiv och om etiska aspekter beaktas. Metod: Kritisk litteraturgranskning med en deduktiv ansats och innehållsanalys med induktiv ansats. Resultat: Forskning gällande digital teknik utgår ofta från forskningscenter som har en teknisk inriktning. Ett högre välbefinnande beskrivs av flera forskare utifrån att det ger en högre prestanda. Majoriteten av genomförda studier utgår från ett teknikcentrerat perspektiv vilket tolkades som att arbetarens hälsa är ett medel för att uppnå en högre produktivitet. Enligt resultatet kan digital teknik användas för att övervaka arbetaren och beräkna arbetarens hälsa med hjälp av AI (artificiell intelligens) i syfte att öka effektivitet och produktivitet. Etiska ställningstaganden tas sällan i beaktande vid studier av digital teknik. Slutsats: Studien indikerar att det finns ett fortsatt teknikcentrerat perspektiv i forskning av digital teknik som används av industriarbetaren. Övervakning och beräkningar av arbetarens hälsa kan sammanfattningsvis beskrivas som ett medel för högre produktivitet, inte som ett mål. Tvärvetenskapligt samarbete avseende digital teknik skulle kunna skapa en bredare förståelse för välbefinnande där hälsan är ett mål och produktiviteten en effekt. Tvärvetenskapligt samarbete gällande digital teknik skulle även kunna öka medvetenheten om hur tekniken påverkar människan ur ett etiskt perspektiv. / Introduction: Digital technologies changes the processes of work and thus can affect work environment. The European Commission's strategy, Industry 5.0, calls for a human-centric approach to digital development that contributes to wellbeing and sustainability. Aim: The aim was to analyze the view of health and wellbeing in studies that invoke Industry 5.0. The research questions seek answers to how wellbeing is described, whether the research is technology- or human-centered and whether ethical aspects are taken into account. Method: Critical literature review with a deductive approach and content analysis with an inductive approach. Results: Research on digital technology is often based on centers that have a technical focus. Higher level of wellbeing is described on the basis that it provides higher performance. The majority of the studies conducted are based on a technology-centered perspective, which is interpreted to lead to the perception that the worker's health is a means to achieve higher productivity. Digital technologies described are used to monitor worker and calculate the worker's health in order to increase productivity. Ethical positions are rarely taken into account. Conclusion: There is a continued technology-centric perspective in research of digital technologies that is intended to improve the wellbeing of the worker. Monitoring and calculating the health of the worker is described as a means to higher productivity. Interdisciplinary collaboration on digital technologies could create a broader understanding of wellbeing where health is a goal and productivity is an effect. Interdisciplinary collaboration could also raise awareness of how technology affects workers from an ethical perspective.

The development of advanced manufacturing opens new possibilities regarding cooperation between robots and humans, leading to a more sustainable industry. The study aims to research how automated processes with collaborative applications can be implemented in manual production systems and analyse the economic and ergonomic consequences this leads to. The process examined in the thesis is the de-labelling of wooden pallets conducted at the case company Volvo Construction Equipment in Braås, Sweden. Both quantitative and qualitative methods have been used. The study started with an analysis of the current situation regarding process design and the ergonomic aspect. The equipment needed to design the robot cell for testing had to be evaluated before a simulation of the automated process was done. Finally, the concept was tested in a laboratory environment. The result of the study shows that it is possible to automate if the removal of the labels is carried out completely perpendicularly. The economic analysis shows that the automated solution becomes a cheaper alternative after one year and four months. When the current manual process consists of unsustainable ergonomic elements, an automated solution will lead to improvements and more sustainable physical and organisational ergonomics. / Utvecklingen av avancerad tillverkning öppnar upp för nya möjligheter med samarbeten mellan människa och robot, vilket leder till en mer hållbar industri. Denna studie syftar till att undersöka hur automatiserade processer med kollaborativa applikationer kan bli implementerade i manuella produktionssystem och analysera de ekonomiska och ergonomiska konsekvenserna detta leder till. Processen som granskats är avtagandet av etiketter från träpallar som genomförts på fallföretaget Volvo Construction Equipment i Braås, Sverige. Både kvantitativa och kvalitativa metoder har använts. Studien började med analys av den nuvarande situationen gällande design av process och den ergonomiska situationen. Utrustningen som behövdes för att designa robotcellen utvärderades innan en simulering av den automatiserade processen gjordes. Seden testades konceptet i laboratoriemiljö. Studiens resultat visar att det är möjligt att automatisera om avtagandet av etiketter genomförs helt vinkelrät från pallen. Den ekonomiska analysen visar att den automatiserade lösningen blir ett billigare alternativ efter ett år och fyra månader. Om den nuvarande manuella processen består av ohållbara ergonomiska element, kommer en automatiserad lösning leda till förbättringar och en mer hållbar fysisk-, kognitiv- och organisatorisk ergonomisk situation.

<p>A thesis study investigating the development and evaluation of a computer vision (CV) system for a manufacturing assembly task is reported. The CV inference results are compared to a Manufacturing Process Plan and an automation method completes a buyoff in the software, Solumina. Research questions were created and three hypotheses were tested. A literature review was conducted recognizing little consensus of Industry 4.0 technology adoption in manufacturing industries. Furthermore, the literature review uncovered the need for additional research within the topic of CV. Specifically, literature points towards more research regarding the cognitive capabilities of CV in manufacturing. A CV system was developed and evaluated to test for 90% or greater confidence in part detection. A CV dataset was developed and the system was trained and validated with it. Dataset contextualization was leveraged and evaluated, as per literature. A CV system was trained from custom datasets, containing six classes of part. The pre-contextualization dataset and post-contextualization dataset was compared by a Two-Sample T-Test and statistical significance was noted for three classes. A python script was developed to compare as-assembled locations with as-defined positions of components, per the Manufacturing Process Plan. A comparison of yields test for CV-based True Positives (TPs) and human-based TPs was conducted with the system operating at a 2σ level. An automation method utilizing Microsoft Power Automate was developed to complete the cognitive functionality of the CV system testing, by completing a buyoff in the software, Solumina, if CV-based TPs were equal to or greater than human-based TPs.</p>