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This book examines the theoretical foundations of the processes of planning and design. When people – alone or in groups – want to solve problems or improve their situation, they make plans. Horst Rittel studied this process of making plans and he developed theories – including his notion of \"wicked problems\" – that are used in many fields today. From product design, architecture and planning – where Rittel’s work was originally developed – to governmental agencies, business schools and software design, Rittel’s ideas are being used. This book collects previously unavailable work of Rittel’s within the framework of a discussion of Rittel’s theories and philosophical influences. Prologue Part 1: Foundations 1.1. Reflections On The Scientific And Political Significance Of Decision Theory 1.2. Science and Design Seminars: Introduction 1.3. Seminar 1: Modes of Innovation 1.4. Seminar 2: Images and Message 1.5. Seminar 3: Communications 1.6. Seminar 4: Establishing Order 1.7. Seminar 5: Measuring Values and Images 1.8. Seminar 6: Environments 1.9. Seminar 7: Design 1.10. Seminar 8: Models of and for Design 1.11. Seminar 9: Models of and for Design 2 1.12. Seminar 10: Conclusion Part 2: Wicked Problems 2.1. On the Planning Crisis Part 3: Design Reasoning 3.1. Structure and Usefulness of Planning Information Systems 3.2. Issues As Elements Of Information Systems 3.3. The Reasoning of Designers Part 4: Consequences of Design 4.1. Technological Change and Urban Structure 4.2. Pathologies of Planning. Epilogue Jean-Pierre Protzen is Professor of the Graduate School at the University of California, Berkeley. He was Horst Rittel’s colleague and collaborator for over twenty years and since Rittel’s death in 1990 has continued teaching Rittel’s work at Berkeley. David J. Harris was Protzen’s student at Berkeley, and his dissertation, \"Design Theory: From Scientific Method to Humanist Practice,\" relied heavily on Rittel’s work. He currently works as an editor and writing coach.

The tools and technique used in the Design of Experiments (DOE) have been proved successful in meeting the challenge of continuous improvement over the last 15 years. However, research has shown that applications of these techniques in small and medium-sized manufacturing companies are limited due to a lack of statistical knowledge required for their effective implementation. Although many books have been written in this subject, they are mainly by statisticians, for statisticians and not appropriate for engineers.Design of Experiments for Engineers and Scientists overcomes the problem of statistics by taking a unique approach using graphical tools. The same outcomes and conclusions are reached as by those using statistical methods and readers will find the concepts in this book both familiar and easy to understand. The book treats Planning, Communication, Engineering, Teamwork and Statistical Skills in separate chapters and then combines these skills through the use of many industrial case studies. Design of Experiments forms part of the suite of tools used in Six Sigma.Key features:* Provides essential DOE techniques for process improvement initiatives* Introduces simple graphical techniques as an alternative to advanced statistical methods - reducing time taken to design and develop prototypes, reducing time to reach the market* Case studies place DOE techniques in the context of different industry sectors* An excellent resource for the Six Sigma training programThis book will be useful to engineers and scientists from all disciplines tackling all kinds of manufacturing, product and process quality problems and will be an ideal resource for students of this topic.Dr Jiju Anthony is Senior Teaching Fellow at the International Manufacturing Unit at Warwick University. He is also a trainer and consultant in DOE and has worked as such for a number of companies including Motorola, Vickers, Procter and Gamble, Nokia, Bosch and a large number of SMEs.

\"Implement Best Practices to Achieve Project Management Excellence The quintessential guide to managing projects, Project Management Best Practices, features comprehensive coverage of the topics of planning, scheduling, controlling, and measuring value within the project management context. With input from senior executives and project managers from over 50 world-class companies, this complete resource is truly the project manager's bible. Author Harold Kerzner provides rare insight into a topic with ever more far-reaching implications for competitive businesses. For middle- and senior-level managers, this compendium of insight from companies like Airbus, Heineken, Dell, IBM, Boeing, and many more will help with implementing the type of project management best practices that add value and efficiency to every level of an organization. The book: Includes the most up-to-date project management best practices Offers new material on the important topics of agile and Scrum Features insights from world-class organizations from Sony to Cisco Also includes instructor resources and handy PowerPoint guides Project Management Best Practices is the perfect resource for upper-level undergraduate and graduate-level courses, as well as an excellence reference for seasoned professionals\"-- Provided by publisher.

In simulation-based realization of complex systems, we are forced to address the issue of computational complexity. One critical issue that must be addressed is the approximation of reality using surrogate models to replace expensive simulation models of engineering problems. In this paper, we critically review over 200 papers. We find that a framework for selecting appropriate surrogate modeling methods for a given function with specific requirements has been lacking. Having such a framework for surrogate model users, specifically practitioners in industry, is very important because there is very limited information about the performance of different models before applying them on the problem. Our contribution in this paper is to address this gap by creating practical guidance based on a trade-off among three main drivers, namely, size (how much information is necessary to compute the surrogate model), accuracy (how accurate the surrogate model must be) and computational time (how much time is required for the surrogate modeling process). Using the proposed guidance a huge amount of time is saved by avoiding time-consuming comparisons before selecting the appropriate surrogate model. To make this contribution, we review the state-of-the-art surrogate modeling literature to answer the following three questions: (1) What are the main classes of the design of experiment (DOE) methods, surrogate modeling methods and model-fitting methods based on the requirements of size, computational time, and accuracy? (2) Which surrogate modeling method is suitable based on the critical characteristics of the requirements of size, computational time and accuracy? (3) Which DOE is suitable based on the critical characteristics of the requirements of size, computational time and accuracy? Based on these three characteristics, we find six different qualitative categories for the surrogate models through a critical evaluation of the literature. These categories provide a framework for selecting an efficient surrogate modeling process to assist those who wish to select more appropriate surrogate modeling techniques for a given function. It is also summarized in Table 4 and Figs.  2 , 3 . MARS, response surface models, and kriging are more appropriate for large problems, acquiring less computation time and high accuracy, respectively. Also, Latin Hypercube , fractional factorial designs and D-Optimal designs are appropriate experimental designs. Our contribution is to propose a qualitative evaluation and a mental model which is based on quantitative results and findings of authors in the published literature. The value of such a framework is in providing practical guide for researchers and practitioners in industry to choose the most appropriate surrogate model based on incomplete information about an engineering design problem. Another contribution is to use three drivers, namely, computational time, accuracy, and problem size instead of using a single measure that authors generally use in the published literature.

The quality control of plastic products is an essential aspect of the plastic injection molding (PIM) process. However, the warpage and shrinkage deformations continue to exist because the PIM process is easily interfered with by several related or independent process parameters. Thus, great efforts have been devoted to optimizing process parameters to minimize the warpage and shrinkage deformations of products during the last decades. In this review, we begin by introducing the manufacturing process in PIM and the cause of warpage and shrinkage deformations, followed by the mechanism about how process parameters, like mold temperature, melt temperature, injection rate, injection pressure, holding pressure, holding and cooling duration, affect those defects. Then, we summarize the recent progress of the design of experiments and four advanced methods (artificial neural networks, genetic algorithm, response surface methodology, and Kriging model) on optimizing process parameters to minimize the warpage and shrinkage deformations. In the end, future perspectives of quality control in injection molding machines are discussed.

Purpose Following the call for awareness of accepted reporting practices by Ringle, Sarstedt, and Straub in 2012, the purpose of this paper is to review and analyze the use of partial least squares structural equation modeling (PLS-SEM) in Industrial Management & Data Systems (IMDS) and extend MIS Quarterly (MISQ) applications to include the period 2012-2014. Design/methodology/approach Review of PLS-SEM applications in information systems (IS) studies published in IMDS and MISQ for the period 2010-2014 identifying a total of 57 articles reporting the use of or commenting on PLS-SEM. Findings The results indicate an increased maturity of the IS field in using PLS-SEM for model complexity and formative measures and not just small sample sizes and non-normal data. Research limitations/implications Findings demonstrate the continued use and acceptance of PLS-SEM as an accepted research method within IS. PLS-SEM is discussed as the preferred SEM method when the research objective is prediction. Practical implications This update on PLS-SEM use and recent developments will help authors to better understand and apply the method. Researchers are encouraged to engage in complete reporting procedures. Originality/value Applications of PLS-SEM for exploratory research and theory development are increasing. IS scholars should continue to exercise sound practice by reporting reasons for using PLS-SEM and recognizing its wider applicability for research. Recommended reporting guidelines following Ringle et al. (2012) and Gefen et al. (2011) are included. Several important methodological updates are included as well.

If you design and develop products for people, this book is for you. The Persona Lifecycle addresses the \"how\" of creating effective personas and using those personas to design products that people love. It doesn't just describe the value of personas; it offers detailed techniques and tools related to planning, creating, communicating, and using personas to create great product designs. Moreover, it provides rich examples, samples, and illustrations to imitate and model. Perhaps most importantly, it positions personas not as a panacea, but as a method used to complement other user-centered design (UCD) techniques including scenario-based design, cognitive walkthroughs and user testing. John Pruitt is the User Research Manager for the Tablet & Mobile PC Division at Microsoft Corporation. Tamara Adlin is a Customer Experience Manager at Amazon.com. For the past six years, John and Tamara have been researching and using personas, leading workshops, and teaching courses at professional conferences and universities. They developed the Persona Lifecycle model to communicate the value and practical application of personas to product design and development professionals. Features* Presentation and discussion of the complete lifecycle of personas, to guide the designer at each stage of product development.* A running case study with rich examples and samples that demonstrate how personas can be used in building a product end-to-end. * Recommended best practices in techniques, tools, and innovative methods.* Hundreds of relevant stories, commentary, opinions, and case studies from user experience professionals across a variety of domains and industries.

Industrial collaborative robotics is an enabling technology and one of the main drivers of Industry 4.0 in industrial assembly. It allows a safe physical and human-machine interaction with the aim of improving flexibility, operator’s work conditions, and process performance at the same time. In this regard, collaborative assembly is one of the most interesting and useful applications of human-robot collaboration. Most of these systems arise from the re-design of existing manual assembly workstations. As a consequence, manufacturing companies need support for an efficient implementation of these systems. This work presents a systematical methodology for the design of human-centered and collaborative assembly systems starting from manual assembly workstations. In particular, it proposes a method for task scheduling identifying the optimal assembly cycle by considering the product and process main features as well as a given task allocation between the human and the robot. The use of the proposed methodology has been tested and validated in an industrial case study related to the assembly of a touch-screen cash register. Results show how the new assembly cycle allows a remarkable time reduction with respect to the manual cycle and a promising value in terms of payback period.