En studie av företagande, ledarskap och genus i hästbranschen. Projektet pågick 2009-2011 med finansiering från Stiftelsen Lantbruksforskning (2,5 milj kr). I projektet medverkade Lena Abrahamsson, Mats Westerberg och doktorand Lena Forsberg.

IFAU och AFA

Rototilt Group AB is a company located in Vindeln that produces and sells tiltrotators, machine couplers and other different excavator accessories. Since Rototilt recently launched a new series of products, and is expanding their factory, they have not been able to assign any workforce on the quality assurance of their new products. Therefore, this project aims at ensuring that quality is maintained, and that the verifications process is streamlined.

The work is based on measuring the time spent on each segment in the verifying process, and to identify the segments that have the largest influence on quality. Thereafter, every type of deviation Rototilt has experienced since launching the Quick Change™ product series was analysed.

It was found that the verification process takes 17 minutes on average, which is a process time Rototilt is aiming to reduce. A compilation of the deviations since the launching of Quick Change™, indicates that the main problems are product quality and lack of documentation. Based on the analysis of process time and type of deviation, a chart with conceptual solutions forms a solid foundation for implementation, which will result in a winwin situation for the operator as well as the company. One solution that stands out is to invest in quick hydraulic couplers. Another solution is to implement In-Process Verification to ensure the quality instead of the current End of Line Testing method. The analysis indicated which parts were crucial for maintaining the quality, and which were crucial for the efficiency. Recommended concepts are based on minimizing investment costs and efforts for implementation and maximizing improvement of the work environment for the operator.

Modul system HH deliver modular storage systems and electrical solutions that can be combined according to the customer's wishes. This thesis combines argues for the importance for companies to keep improving their organization and production to remain competitive. By relating to a holistic view of the development of production environments, the project focuses on improvements for efficiency and social sustainability in the development of production. The project became relevant as the company has discovered difficulties in balancing production in the event of capacity changes and wants to develop rational flows and increase its flexibility. The project is limited to exploring three assembly stations and the operations and flows that belong to the assembly. The project spiral's iterative 3-step development process was chosen for strategic planning. This methodology allowed the work to continue forward despite the lack of data. The first step deals with planning and processes where technology and users were examined. In this planning phase, a Gantt schedule was used in the ClickUp program to plan the project and to-do lists and deadlines could be set. A literature study was conducted to strengthen arguments and raise new ideas. The theoretical overview focuses on areas around production development with a focus on the development of layouts/assembly stations, psychosocial work environment and organizational management. In the second phase of the project, requirements and wishes were mapped. This was done together with the company, the results from this step were then used to evaluate concepts before detailed development. The project also has several parts of the framework that Muther & Wheeler developed called Systematic layout planning. It provided the tools to understand important connections through relationships and proximity analysis. These methods were also used to evaluate the results. Interviews, observations, and 3D modelling were also performed in this phase to gather information and to understand different production structures. Semi-structured interviews were performed with product managers, production designers, production planners. From these methods, I was together with some employees able to conclude that customer order-driven product development is the focus. That production places demand on rapid implementations in production and that modularity means great flexibility needs and fast lead times. We also found opportunities to minimize repetitive and time-consuming steps through development based on the operator's point of view. Concepts were developed through a development process based on proximity analysis, time studies and results from more subjective interviews. The concepts were then evaluated through an evaluation matrix based on formulated future requirements and wishes. The winning concept was developed in more detail and developed iteratively together with staff from the company. The final concept combines a new, more compact layout that considers proximity requirements between stations as well as flows of materials and operators. The final layout also introduces new types of material buffers and action proposals for improved collaboration and communication for increased flexibility.

Case studies and modeling of logistics systems are the basis for the formulation of the content and structure of a reference model for the organization and management of Value Networks as a higher stage of integrated development of supply chains. The definition of a mathematical model for the balance of the Value Network can reveal the characteristics and principles of organization and management of Value Networks.The instrument obtained enables supply chains to assess their level of development and identify the characteristics that should be developed to reach the concept of Value Network, which is based on knowledge development and environmental integration as supports of the same and its competitive position in the global market.

Proper integration into the model of environmental factors ensures that Value Networks are inserted into the objectives of promoting sustainable development. The current concept of logistics flow is extended to incorporate within it the exchange of energy, resources and impacts to the environment.

The research methods used were based on a combination of study and experimentation of cases and the conceptual and mathematical modeling of systems.

Since 2011 Cuba has been updating its economic model, which is marked by a new scenario for enterprise performance. The present research aims to identify the relevant organizational elements that determine the Cuban entities performance in the current economic and social scenario. Has been identified 42 relevant organization elements whose development is a condition for obtaining good results on stagethat complies with current and future changes in the economic model. Each entity requires, according to their characteristics, undertake the development at least in the 42 relevant elements highlighted in the present study.

One of the park and street workers many tools, is the traditional broom. The

broom is used to tidy up surfaces where machines can’t reach, such as; underneath

benches, in corners and smaller areas. Using a traditional broom requires a twisted

and forward leaning body posture that, if performed during an extended time

period, can result in musculoskeletal problems and negative impact on the health.

This project aimed to develop a new cleaning tool to reduce the forward-leaning,

twisted body posture.

This thesis used a product development methodology and a biomechanical

analysis to fulfil, and evidence base the aim. Review of the literature,

biomechanical analysis and benchmarking were used to set requirement

specifications for this project. The project applied David G Ullman's iterative

product development methodology, including brainstorming, quality function

deployment, morphology, Pugh´s matrix and a failure mode effects analysis.

Furthermore, a functional prototype was built as a last step of the development

phase.

Evaluation of the prototype, in comparison to the traditional broom, was

performed using 3D movement analysis (Qualisys motion capture system) and

surface electromyography (Mega 8 channel system) on one test person.

The project resulted in a physically functional prototype that can be used for

similar tasks as a traditional broom. The concept design dictates the user to push

the cleaning tool in front of the body with postural symmetry in all three planes.

The comparison between a traditional broom and the prototype showed a

reduction in muscle activity when using the prototype. Furthermore, the

movement analysis showed a working posture with less forward leaning and back

rotation. Furthermore, the participant could keep neutral angles in the shoulders

and wrists throughout the task. Note that, the biomechanical analyzes was only

made on one test person which is not enough to conclude that the prototype

contributes to a more healthy working posture.

Services are making a huge impact in the business sector especially in the developed countries. As services are customer-centric, there is a need for an enhanced process framework connected to integrated service development. Such a framework should ideally address value propositions meeting specific customer needs in identifying corresponding service offerings. In this context, this thesis aims to explore on how value propositions are defined, developed, and communicated during the introduction of service offerings and to identify the ways to improve the process of value propositions. The work is carried out in the context of a major (Swedish) manufacturing company within a specific product context, namely, the telematics system. The main data collection methods are personal observations, semi-structured interviews, meetings, and company documents. The study seeks to answer three questions: First, what are the value propositions addressed by the current service offerings in telematics system in the context of heavy-duty vehicle equipment? Second, how value propositions are created during the development of these services offerings? Third, how can the service offerings for telematics system be improved through the process of value proposition? The study found that two types of value propositions namely customer value proposition and stakeholder value proposition are addressed by the service offerings in telematics system. Additionally, it is found that value propositions are created in relation to service offerings. Finally, the thesis proposes a six-step conceptual framework to create better value propositions during the development of service offerings. The presented framework is applied to the current value proposition process at the case company and improvement suggestions are proposed, which can impact the service offerings in the near future. The thesis has contributions to enhance or create new service offerings through addressing the value propositions and applying them. The results are beneficial for managers and developers who work in developing the future state scenarios or business models.

The ability to adaptively control manufacturing equipment in cloud environments is becoming increasingly more important. Industry 4.0, supported by Cyber Physical Systems and the concept of on-demand, scalable and pay-for-usage resource-sharing in cloud environments offers many promises regarding effective and flexible manufacturing. For implementing the concept of manufacturing services in a cloud environment, a cloud control approach for the sharing and control of networked manufacturing resources is required. This paper presents a cloud service-based control approach which has a product perspective and builds on the combination of event-driven IEC 61499 Function Blocks and product manufacturing features. Distributed control is realised through the use of a networked control structure of such Function Blocks as decision modules, enabling an adaptive run-time behaviour. The control approach has been developed and implemented as prototype systems for both local and distributed manufacturing scenarios, in both real and virtual applications. An application scenario is presented to demonstrate the applicability of the control approach. In this scenario, Assembly Feature-Function Blocks for adaptive control of robotic assembly tasks have been used.

A developing trend within the manufacturing shop-floor domain is the move of manufacturing activities into cloud environments, as scalable, on-demand and pay-per-usage cloud services. This will radically change traditional manufacturing, as borderless, distributed and collaborative manufacturing missions between volatile, best suited groups of partners will impose a multitude of advantages. The evolving Cloud Manufacturing (CM) paradigm will enable this new manufacturing concept, and on-going research has described many of its anticipated core virtues and enabling technologies. However, a major key enabling technology within CM which has not yet been fully addressed is the dynamic and distributed planning, control and execution of scattered and cooperating shop-floor equipment, completing joint manufacturing tasks.

In this paper, the technological perspective for a cloud service-based control approach is described, and how it could be implemented. Existing manufacturing resources, such as soft, hard and capability resources, can be packaged as cloud services, and combined to create different levels of equipment or manufacturing control, ranging from low-level control of single machines or devices (e.g. Robot Control-as-a-Service), up to the execution of high level multi-process manufacturing tasks (e.g. Manufacturing-as-a-Service). A multi-layer control approach, featuring adaptive decision-making for both global and local environmental conditions, is proposed. This is realized through the use of a network of intelligent and distributable decision modules such as event-driven Function Blocks, enabling run-time manufacturing activities to be performed according to actual manufacturing conditions. The control system’s integration to the CM cloud service management functionality is also described.

Different kinds of uncertainty, such as variations in manufacturing capability and functionality, as well as changes in demand, make up a dynamically changing environment for many manufacturing systems of today. The ability to adapt to these unforeseen changes, through dynamic decision-making as well as dynamic control capabilities based on the use of real-time manufacturing information and intelligence, is vital to be able to perform at a competitive level while reducing unscheduled downtime. The event-driven Function Block (FB) model of the IEC 61499 standard, as opposed to the time-triggered and data-driven concept of IEC 61331, supports this approach, making it possible to handle, in a responsive and adaptive way, different kinds of uncertainty. Our objective is to develop methodologies for distributed, adaptive and dynamic process planning as well as machine monitoring and control for machining and assembly operations, using event-driven FBs. The implementation and testing of FB-based control for manufacturing equipment has been successfully realized in prototype systems, with control of both CNC machining and robotic assembly operations. The approach of using IEC 61499 FBs for adaptive control in other applications is also investigated, as an adaptive decision support system for operators at manufacturing facilities is under development. We strongly believe that IEC 61499 will play a major role in the shift to adaptive manufacturing systems.

Cloud manufacturing has emerged as a new manufacturing paradigm, which combines technologies (such as Internet of Things, Cloud computing, semantic Web, virtualisation and service-oriented technologies) with advanced manufacturing models, information and communication technologies. It aims to be networked, intelligent, service-oriented, knowledge-based and energy efficient, and promises a variety of benefits and advantages by providing fast, reliable and secure on-demand services for users. It is envisioned that companies in all sectors of manufacturing will be able to package their resources and know-hows in the Cloud, making them conveniently available for others through pay-as-you-go, which is also timely and economically attractive. Resources, e.g. manufacturing software tools, applications, knowledge and fabrication capabilities, will then be made accessible to presumptive consumers on a worldwide basis. After surveying a vast array of available publications, this paper presents an up-to-date literature review together with future trends and research directions in Cloud manufacturing.

The interest for implementing the concept of Manufacturing-as-a-Service is increasing as concepts for letting the manufacturing shop-floor domain take advantage of the cloud appears. Combining technologies such as Internet of Things, Cloud Computing, Semantic Web, virtualisation and service-oriented technologies with advanced manufacturing models, information and communication technologies, Cloud Manufacturing (CM) is emerging as a new manufacturing paradigm. The ideas of on-demand, scalable and pay-for-usage resource-sharing in this concept will move manufacturing towards distributed and collaborative missions in volatile partnerships. This will require a control approach for distributed planning and execution of cooperating manufacturing activities. Without control based on both global and local environmental conditions, the advantages of CM will not be fulfilled.

By utilising smart and distributable decision modules such as event-driven FBs, run-time manufacturing operations in a distributed environment may be adjusted to prevailing manufacturing conditions. Packaged in a cloud service for manufacturing equipment control, it will satisfy the control needs in CM. By combining different resource types, such as hard, soft and capability resources, the cloud service Robot Control-as-a-Service can be realised.

This paper describes the functional perspective and enabling technologies for a control approach for robotic assembly tasks in CM, and describes a scenario for its implementation.

The ideas of on-demand, scalable and pay-for-usage resource-sharing in Cloud Manufacturing are steadily attracting more interest. For implementing the concept of Manufacturing as-a-Service in a cloud environment, description models and implementation language for resources and their capabilities are required. A standardized approach for systemived virtualization, servisilisation, retrieval, selection and composition into higher levels of functionality is necessary. For the collaborative sharing and use of networked manufacturing resources there is also a need for a control approach for distributed manufacturing equipment. In this paper, the technological perspective for an adaptive cloud service-based control approach is described, and a supporting information model for its implementation. The control is realized through the use of a network of intelligent and distributable Function Block decision modules, enabling run-time manufacturing activities to be performed according to actual manufacturing conditions. The control system's integration to the cloud service management functionality is described, as well as a feature-level capability model and the use of ontologies and the Semantic Web.

Modern distributed manufacturing within Industry 4.0, supported by Cyber Physical Systems (CPSs), offers many promising capabilities regarding effective and flexible manufacturing, but there remain many challenges which may hinder its exploitation fully. One major issue is how to automatically control manufacturing equipment, e.g. industrial robots and CNC-machines, in an adaptive and effective manner. For collaborative sharing and use of distributed and networked manufacturing resources, a coherent, standardised approach for systemised planning and control at different manufacturing system levels and locations is a paramount prerequisite. In this paper, the concept of feature-based manufacturing for adaptive equipment control and resource task matching in distributed and collaborative CPS manufacturing environments is presented. The concept has a product perspective and builds on the combination of product manufacturing features and event-driven Function Blocks (FB) of the IEC 61499 standard. Distributed control is realised through the use of networked and smart FB decision modules, enabling the performance of collaborative runtime manufacturing activities according to actual manufacturing conditions. A feature-based information framework supporting the matching of manufacturing resources and tasks, as well as the feature-FB control concept, and a demonstration with a cyber-physical robot application, are presented.

Manufacturing companies are striving to remain competitive in the market and maintain their economic growth and productivity. Uncertainties regarding the changes in product demand, workpiece material, product design, and technological advancement, have imposed pressure on manufacturing systems. Market uncertainties force manufacturing companies to be flexible and responsive in producing different parts, by adapting the existing system without the need for a substantial investment. The market is characterized by time variations in product quantities and varieties while manufacturing systems remain inherently fixed. To sustain competitive manufacturing, a company has to adopt to new production requirements and be responsive to market changes quickly. Conscious decisions have to be made for a system to respond to market fluctuations. In order to respond to the dynamic changes, there is a need for developing methodologies that analyse, evaluate and control performance of manufacturing system at the system and/or process levels.

The primary focus of the thesis is to develop a novel generic framework for modelling and controlling manufacturing systems intending for improvement of the performance of manufacturing and make companies more competitive. The framework incorporates the complex interrelations between the process and system parameters, i.e., the dynamics of the system. Thus, provides a quantitative and qualitative analysis for performance evaluation and for optimizing performance of manufacturing system. The generic framework can further be adapted for studying specific manufacturing systems in discrete manufacturing. Three case studies are presented. The case studies are performed in an automotive company where the effect of various levels of control is investigated in manufacturing systems configured as transfer line or as a flexible manufacturing system.

Two aspects of the dynamic nature of manufacturing system are investigated in this thesis: (1) The engineering nature of the system, i.e., the selection of appropriate process parameters to manufacture a product according to the design specification, and (2) The business nature of the system, i.e., the selection of system parameters with respect to the way the product is manufactured. At the process level, the parameters are controlled within the process capability limits to adapt to the changes of the system parameters in response to the market dynamics. At the system level, operational parameters are controlled to satisfy performance criteria.

A case study for resource use analysis during primary processes has also been investigated and presented. The critical operations and the operations that have the highest energy consumptions and the potential for energy savings have been identified.

The methodology developed for analysing the performance of the dynamic manufacturing system is based on a system dynamics modelling approach. Results obtained from different modelling approaches are presented and compared based on the selected performance metrics.

This paper will introduce a novel methodology for the performance evaluation of machining strategies of engine block manufacturing. The manufacturing of engine components is vital to the automotive and vehicle manufacturing industries. Machining is critical processes in the production of these parts. To survive and excel in the competitive manufacturing environment, companies need to improve as well as update their machining processes and evaluate the performance of their machining lines. Moreover, the lines and processes have to be robust in handling different sources of variation over time that include such examples as demand fluctuations, work-piece materials or even any changes in design specifications. A system dynamics modelling and simulation approach has been deployed to develop a methodology that captures how machining system parameters from the machining process are interacted with each other, how these connections drive performance and how new targets affect process and machine tool parameters through time. The developed model could provide an insight of how to select the crucial machining system parameters and to identify the effect of those parameters on the output of the system. In response to such an analysis, this paper provides (offers) a framework to examine machining strategies and has presented model that is useful as a decision support system for the evaluation and selection of machining strategies. Here a system dynamics methodology for modelling is applied to the milling operation and the model is based on an actual case study from the engine-block manufacturing industry.

Our life is strongly linked with the usage of natural resources. With increase in world population and welfare there is an increasing global demand for raw material. Energy is a necessity in everyday life and is often generated using non-renewable natural resources which are finite. Manufacturing is one of the largest energy and material resource consumers. There is great concern about minimising consumption of energy in manufacturing industry to sustain the natural carrying capacity of the ecosystem. This is one of the challenges in today’s industrial world. The paper presents the application of system dynamics theory for modelling and simulation of complex manufacturing processes. The simulations help to understand the intricate nature of the interrelation of process parameter and to make sound decision about minimising the energy losses. Two case studies are presented, one in cylinder head casting processes and the other in crankshaft machining. The developed models provide an insight into how to select critical operations and to identify the effect of various parameters on the energy consumption. Also, the models help to understand how changes of parameters over time affect the behaviour of energy changes. The outcome of this research enables the company to identify potential avenues to minimise energy usage and offers a decision support tool.

To be competitive in a manufacturing environment by providing optimal performance in terms of cost-effectiveness and swiftness of system changes, there is a need for flexible production systems based on a well-defined strategy. Companies are steadily looking for methodology to evaluate, improve and update the performance of manufacturing systems for processing operations. Implementation of an adequate strategy for these systems' flexibility requires a deep understanding of the intricate interactions between the machining process parameters and the manufacturing system's operational parameters. This paper proposes a framework/generic model for one of the most common metal cutting operations-the boring process of an engine block machining system. A system dynamics modelling approach is presented for modelling the structure of machining system parameters of the boring process, key performance parameters and their intrinsic relationships. The model is based on a case study performed in a company manufacturing engine blocks for heavy vehicles. The approach could allow for performance evaluation of an engine block manufacturing system condition. The presented model enables a basis for other similar processes and industries producing discrete parts.

Emerging digital and smart technologies, including wearable and collaborative ones, related to the Industry 4.0 paradigm are playing an assisting, collaborative, and augmenting role for the Operator 4.0, and just as in previous industrial revolutions, the nature of work and the workplace for operators on the shop floor is changing. This literature review aims to look into the impact of digital and smart technologies adoption on the workers’ psychosocial stage under the light of the Operator 4.0 typology. Based on the review conducted, a theoretical framework for assessing the psychosocial impacts (risks) of Industry 4.0 technologies adoption in Operator 4.0 is proposed. The framework can be utilized by company managers, researchers, production engineers, and human resources personnel for carrying out a psychosocial risk assessment of Operator 4.0 in assembly, maintenance, and training operations as these operations get digitally transformed and smartified based on self-report questionnaires. Findings reveal that the nature of work, the social and organizational environment of work, and related individual factors are key categories that might affect the Operator 4.0 psychosocial stage on the shop floor.

“Overworking to death” is a phenomenon that has been noticeable in developing countries. The cause of death is mainly through ischemic strokes. While the victims’ occupations differed, they all shared a common characteristic, being positioned in a sedentary work, ranging from IT workers to doctors. This project’s aim was to develop a product that prevented or decreased the strokes that derived from sedentary overwork. This was mainly tackled by preventing one of the three causes of developing blood props, slowed blood flow. In order to gather rich data of the phenomenon, a qualitative study was conducted in China, during two months. By doing an extensive structured sampling, information rich data could be gathered during a short period of time. Data were derived from observations, questionnaires and an interview, which then was interpreted to customer needs and the final product specification. The final product became a trouser with an in built dynamic compression mechanic, that can compress the veins mostly during sitting activities, in order to prevent blood stasis. The compression mechanic works like the Chinese finger trap; compressing the calves while sitting and stretching the legs forward. It is made only out of polysaccharides fibres; cotton and corn.

This bachelor thesis has been done at Scania CV AB’s department for engine manufacturing in Södertälje. The manufacturing process at the department is currently under development, where two new lines are being added, one for cylinder head and one for cylinder blocks. These two new manufacturing lines are going to be controlled with the help of a Manufacturing Execution System.

The Manufacturing Execution Systems task is to collect data and information from the manufacturing process, which later can be presented in an interface. There is a specification at Scania that presents what information will be available in the system. That specification is in line with what the International Society of Automation has specified in ISA-95.

The specification for the system was set by the IT-department in consultation with department managers. There is currently an uncertainty if the specification meets the requirement that the workers has, to be able to work efficiently with the system. This thesis will identify the requirement that the workers has on the system, and compare it with the current specification.

What the workers deems is necessary information has been identified and mapped through interviews and a survey. The result of these interviews and the survey made it clear that the specification was well in line with the requirement from the workers. This information led to the decision to send out another survey that asked the workers to prioritize how important the information in the system is, in three different priority levels. This resulted in an overview of what the workers consider is the most important information in the system.

This paper presents a decision-support system for reshoring decision-making based on fuzzy logic. The construction and functionality of the decision-support system is briefly outlined and evaluated in a highcost environment contemplating six specific decision criteria, namely cost, quality, time, flexibility, innovation and sustainability. A major challenge with fuzzy logic solutions has to do with the construction of the fuzzy inference rules. In the relocation domain, the fuzzy inference rules represent the knowledge and competence of relocation experts and they are usually created manually by the same experts. One obstacle is that the complexity of the fuzzy inference rules increases with the number of decision criteria. To overcome this complexity issue, this paper presents a solution whereby the fuzzy inference rules are automatically generated by applying one hundred reshoring scenarios as input data. The reshoring decision recommendations produced by the fuzzy logic decision-support system are demonstrated to be close to those of human reshoring domain experts.

Reshoring can be regarded as offshoring in reverse. While offshoring mainly has been driven by cost aspects, reshoring considers multiple aspects, such as higher quality demands, faster product delivery and product mass-customization. Where to locate manufacturing is usually a purely manual activity that relies on relocation experts, hence, an automated decision-support system would be extremely useful. This paper presents a decision-support system for reshoring decision-making building a fuzzy inference system. The construction and functionality of the fuzzy inference system is briefly outlined and evaluated within a high-cost environment considering six specific reshoring decision criteria, namely cost, quality, time, flexibility, innovation and sustainability. A challenge in fuzzy logic relates to the construction of the so called fuzzy inference rules. In the relocation domain, fuzzy inference rules represent the knowledge and competence of relocation experts and are usually generated manually by the same experts. This paper presents a solution where fuzzy inference rules are automatically generated applying one hundred reshoring scenarios as input data. Another important aspect in fuzzy logic relates to the membership functions. These are mostly manually defined but, in this paper, a semi-Automatic approach is presented. The reshoring decision recommendations produced by the semi-Automatically configured fuzzy inference system are shown to be as accurate as those of a manually configured fuzzy inference system. 

Kinnarps is a company that manufactures office furniture and provides workplace solutions for offices and public environments. This project is performed at a manual workstation that packages table legs, this station is responsible for a significant amount of customer complaint costs due to wrong table legs being packaged and sent to the customers. The purpose of this project is to present suggestions for improvement that reduce the risk of packaging errors by using production tools and methods. To achieve the purpose of this project a data collection is to be performed by analyzing historical data and performing observations and interviews. After the data collection the cause of the event is to be found.Theory used to strengthen the choice of methods performed is presented in the theoretical frame of reference. Similar projects have also been studied and are presented in the literature review. The similar projects that were studied can in some way be related to this project and its conclusions.The empirical study was performed by analyzing historical data of the last years customer complaints costs, observations according to the gemba methodology, interviews and conversations with the staff. The costs of customer complaints for the last year was around 723 000 SEK. With the results of the performed methods an Ishikawa diagram was created to identify the causes of the packaging errors. The Ishikawa diagram combined with the theoretical frame of reference and literature review was used to develop three suggestions for improvement that help reduce the amount of customer complaints caused by packaging errors.All suggestions for improvement have been validated by analyzing the effectiveness, cost and the amount of work needed to implement the suggestions. The validations process resulted in a barcode scanner being the most suitable suggestion. By implementing a barcode scanner, the customer complaints could be reduced by an estimate of 92% which corresponds to saving around 665 000 SEK per year in customer complaint costs.

Taper making of boat masts is currently made with high work- and cassation costs. The main reasons are complex settings and varied demand, another is the craft like production method which makes the fixture use low.

Due to a higher demand when new masts are being produced the work cost will sink relative to the turnover given that the workforce is unchanged. This assumes a higher productivity in the fixtures.

To adapt the production to a higher demand and lower cassation costs measures will have to be made. A measure related to lower cassation costs is standardisation of the rail steering. To reduce the time for taper making the measure preloading is the single most affecting measure.

The production of boat masts varies highly over the year with a top rate in spring and bottom rate in the winter. Taper making is also very craft like which makes the volume flexibility low due to the skill of the operators. Currently there are three operators who fully possess the ability. The others, mainly at another function of the mast division, can only relieve the taper operator.

Among the suggested measures open fixture is mentioned in order to reduce the handling of masts. Currently, when handling longer masts, an AGV will have to be stopped by the operator in due to avoid collision. This problem occurs because of the fact that the fixture is being loaded in the length direction of the mast. With a new fixture, capable of cross loading, the time for handling will be reduced but the amount of time is difficult to estimate.

Undersökningens syfte är att se vilka anledningar individen har till att välja friår och hur det kopplas samman med livsformerna de lever. Syftet har också varit att se individens upplevelse av friåret och vad de använt friåret till. Undersökningen bygger på kvalitativa intervjuer med sex friårslediga. Intervjuerna har handlat om individens upplevelse av friåret och tiden före det.

Friår är en arbetsmarknadspolitisk åtgärd med målsättning att ge arbetstagare en längre ledighet från sitt arbete. Arbetslösa får samtidigt en chans att komma in på arbetsmarknaden. Friåret innebär att vara ledig från sitt arbete i tre till tolv månader för att kunna göra något annat utanför arbetsplatsen. För att kunna undersöka av vilka anledningar individen har friår och hur det kopplas med de olika sociala strukturer som villkorar människors vardag. Vi har studerat om livsformsanalysen kan användas till att beskriva, förklara och förstå skillnaderna i människors vardag. Livsformerna är sociala strukturer som villkorar människors vardag. De olika livsformsbegreppen som vi har använt oss av är arbetarlivsformen – husmorslivsformen, karriärenslivsform – representationshustrunslivsform och självständighetens livsform – medhjälperskans livsform. Det är dock vanligt att leva en blandning mellan två eller flera livsformer, det kallas en blandform.

Vi har kommit fram till att livsformerna till viss del kan kopplas samman med hur intervjupersonerna lever under sitt friår och av vilken anledning de har friår. Det visar sig i att de som använder friåret till att starta ett företag lever till stor del självständighetens livsform. Att använda friåret till utbildning kan kopplas samman med karriärens livsformer. Vidare kan vi se att karriärenslivsform kan kopplas samman med att pressen på arbetet är stor och då är rekreation under friåret vanligt. Många kvinnor lever blandformer och det gör att de har svårt att kombinera de olika arbets- och kärleksformerna. De använder friåret till att ta hand om sin familj och sig själva.

In order to successfully move "from products to solutions", companies need to redesign their business model. Nevertheless, service oriented BMs in product-centric firms are under-investigated in the literature: very few works develop a scheme of analysis of such BMs. To provide a first step into closing this gap, we propose a new framework to describe service-oriented BMs, pointing out the main BM components and related PSS characteristics. Thus, the proposed framework aims to help companies to take into account the relevant elements that need to be designed to successfully implement a service-oriented BM and thus guide strategic decisions. (C) 2016 The Authors. Published by Elsevier B.V.

The discussion about business models has gained considerable attention in the last decade. Business model frameworks have been developed in the literature as management methods helping companies to comprehend and analyse their current business logic and guide the deployment of new strategies. In response to calls for a deeper understanding of the application of a business model approach to product-service systems (PSS), this study develops a two-level hierarchical framework that (i) includes a set of components with pertinent, second-order variables to take into account when undergoing the shift from products to solutions; (ii) supports industrial companies, especially SMEs, in designing their future business model and in consistently planning the actions needed to implement it. The framework was applied and refined within real-life settings. The application to KINE - a robot solutions supplier - shows how key challenges faced by servitization firms may be thoroughly addressed through the adoption of a business model perspective.

This paper presents an approach that utilizes artificial intelligence techniques to identify autonomous machine behavior patterns. The context for investigation involves a fleet of prototype autonomous haulers as part of a Product Service System solution under development in the construction and mining industry. The approach involves using deep learning-based object detection and computer vision to understand how prototype machines operate in different situations. The trained model accurately predicts and tracks the loaded and unloaded machines and helps to identify the data patterns such as course deviations, machine failures, unexpected slowdowns, battery life, machine activity, number of cycles per charge, and speed. PSS solutions hinge on efficiently allocating resources to meet the required site-level output. Solution providers can make more informed decisions at the earlier stages of development by using the AI techniques outlined in the paper, considering asset management and reallocation of resources to account for unplanned stoppages or unexpected slowdowns. Understanding machine behavioral aspects in early-stage PSS development could enable more efficient and customized PSS solutions.

Experimental studies helped to compare methods determining and calculating total heat resistance of clothing sets accepted by Russian and international standards. Findings are that difference in the total heat resistance values calculated on humans and on dummies in relatively still air and quiet conditions is caused by measurement technique applied. Significant difference in the total heat resistance values calculated in windy conditions or during walk require further research aimed to study influence of those factors on clothes' heat resistance

The relationship between a product and a manufacturing system is addressed in various engineering design theories. The different approaches in the engineering design field are mainly focused on product design. The purpose of this paper is to review theories in the area of engineering design, in order to discuss applicability of engineering design theories on the concurrent product and manufacturing system development. The reviewed theories are: Axiomatic Design, Robust Design, Theory of Domains, and Theory of Technical Systems.

Autoliv Sverige AB är ett företag som ligger i Vårgårda och tillverkar airbagar, gasgeneratorer samt elektronik till radarsystem. I framtiden finns planer för att expandera produktionen men i dagsläget vet företaget inte hur mycket resurser som går åt för materialflödet till de olika produktionslinorna. För att ta reda på hur mycket personella resurser som behövs både i befintligt materialflöde och i framtida produktionslinor vill företaget undersöka systemet som matar fram material till produktionen. För att ta fram ett verktyg som gör detta används aktionsforskning som huvudmetodik. Aktionsforskning utgör en iterativ process som består av observationer, framtagning av lösningsförslag och utvärdering av lösningsförslag. Observationerna genomfördes i samband med datainsamlingen där Kanbanrundan undersöktes, definierades och mätetal togs fram. Detta för att få en grundförståelse för vad innehållet i verktyget skulle vara.Nästa steg i processen var framtagning av lösningförslag, vilka skapades med hjälp av benchmarking av interna dokument och informationen som samlats från observationerna. En konceptmodell per person skapades och ett koncept valdes sedan ut som utgångspunkt för fortsatt utveckling av verktyget. Modellen blev sedan granskad respektive förbättrad av medlemmarna och handledaren på företaget i en iterativ process.När modellen ansågs klar verifierades det mot verkligheten och den insamlade datan. Verktyget validerades sedan genom att en anställd på Logistikavdelningen fick testa det. Utöver utvecklandet av verktyget och insamlingen av datan utfördes en benchmarking både internt på företaget och externt på ett annat företag för att studera olika materialhanteringsprocesser.I analysen diskuterades för- och nackdelar med olika val och iakttagelser som gjorts, både i arbetssättet för detta examensarbete och dess olika delar men också för materialhanterarens arbetssätt och instruktioner. Resultatet av arbetet blev ett verktyg som uppfyller de krav som formulerades i början av arbetet. Utöver verktyget upptäcktes även ett flertal förbättringsmöjligheter kring materialflödet och produktionen.

Industry 4.0 and the development of novel digital technologies is forcing manufacturing companies to introduce drastic changes to their productions systems. These technologies provide unique opportunities for manufacturing companies to collect, process and store large data volumes, which can be used to facilitate the coordination of factory elements. Previous research indicate that decisions based on data can provide fact-based decisions which can contribute to an increased productivity. However, manufacturing companies are not fully exploiting data as support for decision-making, which is desirable for an increased competitiveness. Currently, much attention is pointed towards the technology instead of the humans responsible for interpreting data and making decisions. Adding to this, there is a lack of guidance on how manufacturing companies can go from current decision making practices (i.e., decisions based on gut feelings) to fact-based decisions driven by data. To address this gap, the purpose of this thesis is to propose a framework for achieving data-driven decision making in production development in the context of Industry 4.0. The purpose is accomplished by using a qualitative-based case study approach at a small and medium sized enterprise in the electronics industry. The results indicate that both challenges and enablers for achieving data-driven decision making in production development are related to perspectives and attitudes, processes for data quality, technology and processes for decision making. Four maturity levels of data-data driven decision making are also identified. The proposed framework can be used by manufacturing companies to help them plan and prepare for their own specific development path towards data-driven decision making. Contributing to current understanding, this thesis considers the human decision makers perspective to develop the ability to collect, process, analyze and use the data to support time efficient and high-quality decisions, an insight lacking in prior academic studies. Future research may include confirmation of the findings presented in this thesis with additional use cases and industry types.

With the development towards Industry 5.0, manufacturing companies are developing towards smart production. In smart production, data is used as a resource to interconnect different elements in the production system to learn and adapt to changing production conditions. Common objectives include human-centricity, resource-efficiency, and sustainable production. To enable these desired benefits of smart production, there is a need to use digital technologies to create and manage the entire flow of data. To enable smart production, it is essential to deploy digital technologies in a way so that collected raw data is converted into useful data that can be applied by equipment or humans to generate value or reduce waste in production. This requires consideration to the data flow within the production system, i.e., the entire process of converting raw data into useful data which includes data management aspects such as the collection, analysis, and visualization of data. To enable a good data flow, there is a need to combine several digital technologies. However, many manufacturing companies are facing challenges when selecting suitable digital technologies for their specific production system. Common challenges are related to the overwhelming number of advanced digital technologies available on the market, and the complexity of production system and digital technologies. This makes it a complex task to understand what digital technologies to select and the recourses and actions needed to integrate them in the production system.

Against this background, the purpose of this licentiate thesis is to examine the selection and integration of digital technologies to enable smart production within manufacturing companies. More specifically, this licentiate thesis examines the challenges and critical factors of selecting and integrating digital technologies for smart production. This was accomplished by performing a qualitative-based multiple case study involving manufacturing companies within different industries and of different sizes. The findings show that identified challenges and critical factors are related to the different phases of the data value chain: data sources and collection, data communication, data processing and storage, and data visualisation and usage. General challenges and critical factors that were related to all phases of the data value chain were also identified. Moreover, the challenges and critical factors were related to people, process, and technology aspects. This shows that there is a need for holistic perspective on the entire data value chain and different production system elements when digital technologies are selected and integrated. Furthermore, there is a need to define a structured process for the selection and integration of digital technologies, where both management and operational level are involved. 

With the development towards Industry 5.0, manufacturing companies are developing towards Smart Production, i.e., using data as a resource to interconnect the elements in the production system to learn and adapt accordingly for a more resource-efficient and sustainable production. This requires selecting and integrating digital technologies for the entire data lifecycle, also referred to as the data value chain. However, manufacturing companies are facing many challenges related to building data value chains to achieve the desired benefits of Smart Production. Therefore, the purpose of this paper is to identify and analyze the critical factors of selecting and integrating digital technologies for efficiently benefiting data value chains for Smart Production. This paper employed a qualitative-based multiple case study design involving manufacturing companies within different industries and of different sizes. The paper also analyses two Smart Production cases in detail by mapping the data flow using a technology selection and integration framework to propose solutions to the existing challenges. By analyzing the two in-depth studies and additionally two reference cases, 13 themes of critical factors for selecting and integrating digital technologies were identified.

In the intermittent turning and milling processes, during the entry phase the cutting edges are subjected to high impact loads that can give rise to dynamical and strength issues which in general cause tool life reduction. In this study the effect of geometrical features of the cutting tool on the force generation during the entry phase is investigated. Cutting forces are measured by a stiff dynamometer at a high sampling frequency. In addition, the chip load area is analyzed and related to the measured cutting force. The results show that micro-geometrical features, in particular the protection chamfer, significantly affect the force generation during the entry phase.

In the intermittent turning and milling processes, during the entry phase the cutting edges are subjected to high impact loads that can give rise to dynamical and strength issues which in general cause tool life reduction. In this study the effect of geometrical features of the cutting tool on the force generation during the entry phase is investigated. Cutting forces are measured by a stiff dynamometer at a high sampling frequency. In addition, the chip load area is analyzed and related to the measured cutting force. The results show that micro-geometrical features, in particular the protection chamfer, significantly affect the force generation during the entry phase.

The aim of this study was to investigate the effect of the welding heat input on the heat affected zone (HAZ)in AA6005-T6 aluminium alloy for a butt-welded joint using gas metal arc welding by evaluating the thermal cycles, metallography and the resulting mechanical properties in the zone. This study involved using a welding experiment, numerical simulation, physical simulation and mechanical tests. The welding was carried out using the pulsed gas metal arc welding (GMAW) transfer and type J thermocouples were used to get the thermal cycles in the HAZ. Simufact® Welding was utilised for the numerical simulation. Optical microscope was used to evaluate the microstructures and Vickers microhardness test was done along the weld cross-section. The thermal cycles of thealuminium alloy and a thermal model for the experimental setup was developed. The HAZ was located on the weld cross-section with a mean hardness of 63.7HV0.1, which is considerably lower when compared with the base metal which has a hardness of 100HV0.1. This indicates thermal softening occurred due to the heat input to the material. There is a match in the hardness values of the Gleeble samples and the locations on the weld cross section suggested by the model showing validity of the simulation. This thesis work isused to assess the implications of heat input in aluminium weld joints, identify the HAZ and its mechanical properties in the design of welding process parameters for automobile parts. The Welding parameters can be optimized to reduce the amount of heat input into the weld as this will directly affect the mechanical properties int he HAZ.

Visibility across supply chains has been a key concern for organisations for many years, but the tools and information systems to achieve real-time visibility have not been available until recently. In response to uncertainty and complexity, advanced information and communication technologies have been explored for supply chain visibility (SCV). However, managerial perspectives are largely absent from the current literature. In response, this paper systematically documents managerial factors influencing SCV and information that should be collected and shared among supply chain partners for better visibility. A multi-stage Delphi analysis was conducted with 26 supply chain experts from various globally recognised enterprises with manufacturing units located worldwide. The results provide details on prioritised managerial perspectives and experiences within (1) factors affecting SCV (drivers, enablers, challenges and contingencies), (2) SCV content (supplier, internal and customer information) and (3) implications of SCV (capabilities and performance effects). One observation was that forecasting is not deemed as important due to severe disruptions in supply chains. Real-time visibility for better predictability emerged as the top priority. This study is among the few that empirically explores factors influencing supply chain visibility and generates new insights into why barriers can be difficult to overcome in complex supply chain settings.

Visibility in production logistics and across the supply chain has become a key concern for organizations. Its need has been further emphasized due to the current COVID 19 crisis. Organizations find it challenging to prepare the internal logistics and supply chain, and quickly respond to such unexpected events, due to low visibility. Against this backdrop, the paper, which is a work-in-progress, systematically documents different factors influencing supply chain visibility and crucial information that should be collected and shared among supply chain partners for better visibility. A Delphi analysis is being conducted with twenty-six supply chain experts from various globally recognized enterprises with manufacturing units located worldwide. The study starts with a short open-ended questioner to collect a comprehensive list of antecedents, drivers, barriers, effects, and visibility information based on the qualitative response from the experts. The preliminary results from the first round of the Delphi analysis indicate that risk management, environmental sustainability, and supply chain control are some of the key drivers. Lack of IT infrastructure and maturity are some of the barriers, integrated systems, and technology maturity are among the key antecedents and gaining planning capability and better customer service are some of the positive effects of supply chain visibility as per the experts’ opinion. In addition, information related to planning, supplier location, and deviation are among the crucial ones that require the collection and sharing for better supply chain visibility. This research study is among the few that empirically explores factors influencing supply chain visibility and generates new insights as to why the barriers can be difficult to overcome in complex supply chain settings.

Globalization, escalating competition, and demand for sustainable practices have required supply chain and production managers to consider various capabilities and value creation strategies for the customers. Rapid technological advancement in the current production environment calls for integrative and collaborative efforts for effective resource utilization and better visibility to gain competitive advantages. However, privacy risks and trust have always been a significant barrier for organizations’ efforts towards supply chain integration. Supply chain stakeholders fear these collaborate practices might weaken their bargaining power, accelerate risk of data manipulation and result in loss of information advantages. Addressing these issues, the study proposes a Blockchain-based collaborative model for production visibility and resource sharing. It demonstrates the framework for stakeholders’ interaction over a central procurement system backed with blockchain technology. The study further lays down the notion of production capacity backed smart contract rules. These smart contracts will run on the proposed blockchain network to reduce the possibilities of fraudulent transactions and capacity overbooking- leading to illegitimate subcontracting. The overall network will stimulate visibility and develop a technology-based trust among partners which ensuring sustainability by effective utilization of resources.

Traceability has emerged as a prime requirement for a multi-tier and multi-site production. It enables visibility and caters to the consumer requirements of transparency and quality assurance. Textile and clothing industry is one such example that requires traceability implementation to address prevailing problems of information asymmetry and low visibility. Customers find it difficult to access product data that can facilitate ethical buying practices or assure product authenticity. Besides, it is challenging for stakeholders to share crucial information in an insecure environment with risk of data manipulations and fear of losing information advantage. In this context, this study investigates and proposes a blockchain-based traceability framework for traceability in multi- tier textile and clothing supply chain. It conceptualizes the interaction of supply chain partners, and related network architecture at the organizational level and smart contract and transaction validation rules at the operational level. To illustrate the application of the proposed framework, the study presents an example of organic cotton supply chain using blockchain with customized smart contract and transaction rules. It finally demonstrates the applicability of the developed blockchain by testing it under two parameters. The proposed system can build a technology-based trust among the supply chain partners, where the distributed ledger can be used to store and authenticate supply chain transactions. Further, the blockchain-based traceability system would provide a unique opportunity, flexibility, and authority to all partners to trace-back their supply network and create transparent and sustainable supply chain. 

Digitalization is an upcoming trend that divides the manufacturing industry of today. As an increasing number of companies chose to implement digitalization as a business strategy, some companies still struggle with implementing digitalization into their businesses.

Previous research has developed digital transformation models, but has been admitted as too generic. This thesis used the most comprehensive transformation model as base and aimed to make it practically implementable for a manufacturing company with a process layout. To enable this, a case study was conducted on a steel-processing company with this layout design. This thesis had an inductive approach, where primary data were collected from one selected company through a pilot study and semi structured interviews, and secondary data were collected through a literature review.

During the study, it was discovered that a company can benefit from using a customized guidance of how to implement digitalization, to optimally use digital opportunities. This thesis contributed with additional steps and extensions of the previous transformation model. The contribution consisted of the involvement of competency, creation of definition, identified digitalization trends relating to a SWOT analysis, additional phenomenon to take into consideration when analyzing future scenarios, additional questions to consider when analyzing impacted areas, creation of a digital business strategy, a comparison of impacted areas with previous projects, additional identified actions to fill the gap between current state and goals, and five identified criteria’s on how to prioritize these actions. This study extends current research with details and depth regarding a digital transformation model, and hence make it more practical. For future research, a case study testing the potential of the transformation model on a similar company should be conducted, and thereby improve the model further.