Building Capabilities for Service Innovation

The service sector is the most dominant sector in every developed economy today. The ability to develop and successfully launch new services is crucial for service organizations to stay competitive and to adapt to the ever-changing conditions of the environment. However, up until now, a mismatch remains between the importance of service innovation for society and the attention given to it in both academia and practice. Existing research has compared the innovative output of service firms with manufacturing firms and found that the difference is one of degree rather than of substance. Studies which focus on the process instead of the output of service innovation, however, are still relatively scarce. This dissertation aims to help close this research gap by examining three service innovation processes in different contexts. First, it offers a theoretical illumination of service innovation with the help of knowledge creation theory. This is beneficial for defining service innovation more precisely. The second study is concerned with the influence of emotional factors on the development of dynamic capabilities in new ventures. It shows that young ventures which are able to deliberately switch between emotional and analytical modes of operation have a higher likelihood of success. The study compares the development of two service-oriented ventures with two product-oriented ones that are part of an accelerator program at the School of Design Thinking at Stanford University. The third paper is concerned with product-service strategies, or Servitization, and the relation to vertical integration and the coordination of innovation in downstream markets. The study shows that the Servitization development, i.e. the vertical integration of manufacturing firms into its users' operation, is a response to the failure of architectural innovation in more flexible buyer-supplier relationships. The study finds four different strategies for the service business of manufacturing firms based on case studies in the mechanical engineering, electrical engineering, and chemical industries. Overall, I am able to show that firms need to be able to build three distinct capabilities to master their service innovation efforts. First, they need to build up a capacity for innovation to gain economies from partial repetition of solutions. Second, firms need to have skills in place to create and manage boundary objects, especially at the client interface. Finally, they need to have capabilities to build up complementarities which help protect revenues from their service innovation initiatives.

Human-centered Innovation Processes

Alan Cabello Llamas

For more than a decade managers, academics, educators and politicians have indicated that innovation is the key to our future. As a result, we find a plethora of innovation initiatives around the world, from university curricula to the mission statements of banks. This push to innovate is a direct result of the recent economic downturn as well as from an ever more competitive, connected and dynamic world. In order to remain relevant in such a world, emphasis is given to generating new ideas that may lead to new products and services. Despite these initiatives, evidence indicates that investment in innovation does not correlate with success. Although the goal of innovation is clear, the processes whereby that goal may be accomplished are varied and not entirely understood. The motivation of this thesis, therefore, is to gain a better understanding of some of those innovation processes. In recent years, a growing number of firms, organizations and governments have adopted an approach to innovation that is referred to as âDesign Thinkingâ. They use the term to describe the process by which a multifunctional team tackles a problem by exploring the underlying needs of the people most affected by that problemâwhether that be customers, users, etc.âthen, based on these observations, defines the root cause or key elements of the problem and finally attempts to resolve it through an active cycle of ideating, prototyping and testing potential solutions. While the process itself is well defined and understood, its implementation and use by managers in the context of innovation management calls for further exploration. With this objective, I first conducted research within academic literature, followed by an ethnographic study focused on the use of Design Thinking by both large firms and entrepreneurial teams. The first paper of this dissertation examines the different elements in the Design Thinking process within the context of management research. The goal of the first conceptual article is thus to establish the common ground among diverse subfields of research in management upon which future research in Design Thinking may build. The second paper of this dissertation aims to uncover how large firms use Design Thinking as an approach to innovation. Based upon direct observation and interview data we find evidence of links between Design Thinking and Absorptive Capacity. We therefore propose that Design Thinking may be a helpful tool for firms who wish to innovate by an increase in their Absorptive Capacity. The third and final paper of this dissertation aims to understand the effects of Design Thinking on the venture creation process. This work is based on ethnographic research conducted at Stanford University wherein twelve teams participated in an accelerator program that uses a Design Thinking approach with the goal of creating and launching new ventures. Building on Dynamic Capabilities literature, this research finds that the teams with greater capability to iterate their venture concept through repeated cycles of attachment and detachment relative to their proposed products or services tend to be more successful.

EPFL2015

Modeling and Simulation of Energy Efficient Milling Process Plans for Prismatic Parts

Nenad Nesic

The milling process has been continuously optimized from many aspects: forces, velocities, stability, quality. Numerous papers have been published that report results in the domain of toolpath optimization with criteria such as raising the quality of the machined part, obtaining a stable machining process and maximizing the material removal rate. However, only recently researchers have started investigating the ecological impact of machining processes. With the constantly increasing prices of electrical energy and all environmental problems caused by the production and waste of the energy, it has become indispensable to look for ways to optimize machining processes from the energy consumption aspect, too. It is in this domain, then, that the work described in this dissertation contributes – to add a new criterion for the sustainable operation of machine tools: reducing the energy consumption during the use phase of the machine tool. The total energy spent in a machining process is the sum of power spent by all machine tool subsystems multiplied by the time that they are working. Therefore, the operating strategies for increasing energy efficiency for the high-speed machining processes must be oriented towards the reduction of the total machining time (productive and unproductive) and reduction of instantaneous consumed power in the machining process or, preferably, both. There are many causes for milling process time and energy inefficiency. The major sources of potential time reductions include: (i) the issues related to the geometry and topology of the toolpath („air-time”, overlapping segments, gouge and uncut regions, orientation of the toolpath), (ii) the issues related to the kinematics of the feed drives (the feed velocity/acceleration profile). The possible domains for power consumption reduction are related to the forces that exist in the machining process (cutting, inertial, gravitational and friction forces). The power invested to overcome the cutting force is necessary for the machining process but its consumption should be optimized through constant cutting engagement and feedrate scheduling strategies. The other forces are responsible for the pure mechanical power loss and they should be minimized. The optimization variables for inertial and gravitational forces include the feed motion profile and moving mass configuration, while friction losses are load and/or velocity dependent. In addition, there are some power losses in the electric components of machine tool drives (electrical power losses), whose dependency on velocity and mechanical load can also be modeled. Despite many research efforts to analyze and model the phenomena causing inefficiency of the machining process, they are usually not taken into account during milling process planning. In fact, rare are the attempts to use this knowledge to optimize the milling process with more than one of the above mentioned criteria. The reason for that lies in the fact that increasing the instantaneous values of tool engagement and feedrate in order to minimize total machining time also increases the consumed power and, indirectly, deteriorates the tool and/or destabilizes the cutting process. The existence of conflicting criteria in the objective functions imposes the use of evolutionary algorithms for multiobjective optimization. The process of experimental validation of such an optimization model requires costly and complex external hardware setup and it is also time consuming. Hence, there is an emerging need for the development of an accurate model, which would be used for the simulation of the milling process and testing the competing optimization strategies. The ultimate goal of contemporary manufacturing science and engineering is the development of a holistic virtual machine tool system. The motivation of this PhD research is to contribute to this objective by developing the “virtual milling process for prismatic parts (produced by 2.5D milling)”. This category of objects is selected, because the majority of CNC milling tasks can be performed using 2.5D milling. A very large number of mechanical parts are prismatic (their geometry consists exclusively of features that represent 2D contours extruded in a perpendicular direction). Parts that are even more complex are usually produced from a blank by a 2.5D roughing and 3D–5D finishing. Therefore, development of an accurate model of a 2.5D milling process represents a significant contribution to manufacturing engineering. Starting with above given problem description, we have defined the following research objectives: 1. Model power and energy consumption of a 2.5D milling machine as a function of the toolpath geometry (curvature and continuity), cutting engagement, real feedrate profiles and spindle rotational speed, taking into account moving mass configuration, all power losses (mechanical and electrical) in feed-axis and spindle drives and electromechanical constraints of servo drives; 2. Design an integrated software environment for simulation of the developed models; 3. Validate the model experimentally; 4. Demonstrate the potential of its use for multi-objective process optimization. Cutting engagement calculation is performed by using two competing methodologies, in order to make a comparison of their performances. The first one, the pixel based method, is based on discrete image processing, while the other, the exact method, is based on Boolean operations and vector geometry. The tests performed in more than 20 feature/toolpath combinations demonstrate that the exact method is more precise whereas the pixel-based method is computationally much faster. The machine tool operator commands a constant feedrate value. During the process, based on his/her subjective judgment, he/she can manually tune it to keep the process in the desired boundaries. One of the objectives of this research is to predict the real feedrate values so that they can be integrated in the part program before the process start. The feasible profiles of feed velocities for each toolpath segment are analyzed by answering the following questions: can the commanded feedrate be achieved and with what sequence of acceleration and deceleration phases, how much the tool has to slow down in corners and how does the feedrate profile degenerate in segments where the commanded feedrate cannot be reached? In order to determine all forces and torques, a machine tool model is developed. The following subsystems are modeled as rigid bodies (without vibrations): feed motor shaft, transmission, lead screw/nut pair, lead screw bearings, guides (sliding and rolling design), table with the workpiece and electrospindle (rotor, stator and bearings). All kinetic variables (linear and angular speeds; cutting, inertial and friction forces and torques) are then calculated in the joints of this multi-body system. The modeling of all speeds, forces and torques that occur in the machine tool system during the machining process, allows for calculation of various indicators of process time and energy efficiency: material removal rate, total machining time, useful power (invested in cutting), power loss due to the friction in the joints, power losses in electrical motors, electrical energy consumption of feed and spindle drives. In order to assess the accuracy and the reliability of the developed model two sets of experiments have been performed. The model validation is performed on several subsystem levels and the simulation results show a very good compliance with the experimental results. The first experimental setup consists of the force dynamometer, to measure cutting force components in linear axis directions, two laser optical position sensors, to measure the real feedrate and the power sensor, to measure the total power consumption of the machine tool electrical motors. The machining process was performed on the 6-axis machining center C.B. Ferrari A152 and the data acquisition platform was developed in LabVIEW 2010. The second experimental setup consists of the torque dynamometer, to measure the cutting torque directly on the spindle, the built-in current sensor that measures the motor current proportional to the electrical power consumed by the spindle and, again, the power sensor, to measure the total power consumption of the machine tool electrical motors. This time, MIKRON HPM 600U, a 5-axis milling machine equipped with the controller iTNC530, was used for the experimentation. The developed model is ready for practical implementation. Several examples have been prepared to demonstrate its capabilities in the domains of milling process simulation, sensitivity analysis and prospective optimization strategies. These examples include the prediction of various kinetostatic variables for given toolpaths, choice of the optimum machining strategy (minimization of machining time, moving mass and energy consumption) and process optimization by feedrate scheduling (reduction of cutting force fluctuation). As a conclusion, the major contribution of this PhD research is the development of a comprehensive rigid-body dynamics model of a machine tool system, aimed for the generation, simulation and optimization of 21⁄2D milling process plans. The model features several novelties compared to existing approaches: (i) it takes into account the machine tool rigid body dynamics and real tool kinematics in toolpath planning, (ii) it predicts all mechanical and electrical power losses in the machine tool system (iii) it allows the modeling of machine tool system electromechanical constraints. The model was experimentally validated on two real machine tools in different workshops and its capabilities for the simulation of different toolpath patterns and optimization of process parameters were successfully demonstrated using several examples.

EPFL2012

Determinants of PhD holders' use of social networking sites: An analysis based on LinkedIn

Stefano Horst Baruffaldi

Social networking sites are an increasingly important tool for career development, especially for highly skilled individuals. Moreover, they may constitute valuable sources of data for scholars and policy makers. However, little research has been conducted on the use by highly skilled individuals of those social networks. In this paper, we focus on PhD graduates, who play an important role in the innovation process and in particular in knowledge creation and diffusion. We seek to increase understanding of the determinants that induce PhD graduates to register on LinkedIn and to develop wider or narrower networks. Controlling for the most relevant individual characteristics, we find that (i) PhD holders moving to the industry sector are more likely to have a LinkedIn account and to have a larger network of connections in LinkedIn; (ii) PhD holders are more likely to use LinkedIn if they have co-authors abroad; and (iii) they have wider networks if they have moved abroad after obtaining their PhD. In light of our analyses, we discuss the usefulness of - and main concerns about - the adoption of LinkedIn as a new data source for research and innovation studies. (C) 2017 Elsevier B.V. All rights reserved.