Romain Farel

The UNPC innovativeness set of indicators for idea or project selection and maturation in healthcare

Abstract A great deal of work has been done to characterize entire sets of ideation indicators as well as isolated factors of innovativeness. Nevertheless, entire sets of innovativeness indicators are essential in business innovation competitions, as well as within companies in order to select promising innovation seeds. In this paper, a complete set of innovativeness indicators in the context of innovating in healthcare is proposed. The UNPC innovativeness model, standing for usefulness, newness, profitability and (proof of) concept, has been tested and validated over a period of 4 years within the largest European innovation cluster in the silver economy. Four authentic examples of innovation selections are analyzed. They illustrate how the UNPC model is able to provide clear and efficient guidance for better decision-making in the context of innovating for the elderly. In addition, a framework for monitoring an innovative idea or project, and for increasing its maturity, is proposed. The UNPC monitoring process starts with the Strengths, Weaknesses, Opportunities, and Threats analysis of competing ideas. It then becomes dynamic, looking for new evidence for increasing the certainty and impact of UNPC proofs of the competing ideas. The model has been successfully used for upgrading a popular smart application on activity tracking.

Usefulness Simulation of Design Concepts

Usefulness, from the utilitarianism perspective, is the ability of a product or service to improve the well-being of humans and to minimize their suffering in different situations. In the case of the widespread issue of falls among the elderly, designing an adapted solution to is not an obvious task. The latter requires quantifying various usage scenarios. The usage scenarios, or segments, associated with elderly falls must be investigated to ensure that newly designed products and services are likely to bring essential health, social, and economic values. Optimizing a design solution by considering the coverage of such usage segments extends the classical methods of design for market approaches. Starting from a disparate literature on elderly falls’ issue, we have first built a usage scenarios space. Next, the usefulness and the coverage ability of three design solutions are evaluated over a tessellation of usage segments. In addition, the developed usage simulator is used to assess the potential of non or poorly covered usage segments to deliver insightful information in order to truly be a need seeker in the front-end of innovation.

A Conceptual Framework for Eco-Industrial Parks

An eco-industrial park is a set of businesses that share resources in order to increase profitability and reduce environmental impact. The implementation of eco-industrial parks may significantly contribute to the creation of a sustainable economy. Despite this prospect, the actual development of eco-industrial parks is challenging, as a variety of factors must be considered. Not only technical, economic, and environmental factors are relevant but numerous stakeholder relationships as well, such as between firms, governmental bodies, and local communities. This paper presents a conceptual framework that is used to capture these diverse aspects and the relationships between them. The Unified Modeling Language (UML) is used for modeling its concepts and relationships. First, based on a literature survey, relevant concepts of eco-industrial parks are identified. One central concept is “industrial symbiosis”. A novel value-based interpretation of industrial symbiosis is presented. Second, the park’s economic, local and regional development context, as well as its internal technical components and their relationships are modeled. Finally, the framework is used for modeling a concrete eco-industrial park, in this case part of the Kalundborg eco-industrial park.Copyright

Capturing the relevant problems leading to pain- and usage-driven innovations: The Dependency Structure Modeling Value Bucket algorithm:

The Dependency Structure Modeling Value Bucket tool is integrated into Radical Innovation Design methodology in order to explore the front end of innovation in need seeker mode. The determination of innovation opportunities, here called value buckets, has been automated by matrix representations of dependencies among problems or pain points, usage situations, and existing solutions. Three matrices are built along the problem-setting stage of a Radical Innovation Design process. The first matrix expresses which problems occur during usage scenarios, the second how far existing solutions cover problems, and the third to what degree existing solutions are useful in usage situations. Combining these three matrices results in a matrix of value buckets, which represents the combinations of important problems which occur during characteristic usage situations and for which few existing solutions are useful or efficient. This outcome allows focused creativity workshops to be run, resulting in usage innovations with a high likelihood of market success.

The DSM Value Bucket Tool

The Dependency Structure Modelling Value Bucket (DSM-VB) tool is integrated to Radical Innovation Design (RID) methodology for exploring the front end of innovation in need seeker mode. The determination of value buckets has been automated by matrix representations of dependencies between problems or pain points, usage situations and existing solutions. Three matrices are built along the problem setting stage of a RID process. The first matrix expresses which problems occur during usage scenarios, the second how much existing solutions cover problems and the third how much existing solutions are useful in usage situations. Combining these three matrices results in a matrix of value buckets as being the combinations of important problems occurring during characteristic usage situations and for which few existing solutions are useful or efficient. This outcome allows to perform focused creativity workshops and to result in “blue ocean” innovations with high likelihood to be successful on the market.

Estimating Reliability Bounds on Industrial Plants

Reliability analysis is particularly relevant for industrial plants where plant failures can lead to large financial losses. Existing reliability analysis approaches mostly rely on heavyweight simulations that are computationally expensive and require extensive modeling effort. On the other hand, there is an industrial need for quickly evaluating plant reliability for developing new services and business models. In this paper, we extend and apply the reliability bound approach using linear programming to address this need. The reliability bound approach is based on a system model in the form of a graph, an event vector, and estimates for component reliabilities. Based on this model, lower and upper reliability bounds are calculated by solving a linear programming problem. The advantage of this approach is the ubiquity of solvers for linear programming. Furthermore, the approach is guaranteed to produce the narrowest bound with respect to the reliability data. We demonstrate the applicability of the approach to a subsystem of an industrial plant as a test case. Future work consists applying the method to whole plants and comparing the results with simulation-based approaches. Moreover, the approach is planned to be extended to system attributes such as buffers and multiple failure states.

A DATA-AND KNOWLEDGE-DRIVEN METHODOLOGY FOR GENERATING ECO-INDUSTRIAL PARK ARCHITECTURES

Industrial symbiosis can be understood as the substitution of new resources used in an industrial process by another resource that would otherwise be discarded. Industrial symbiosis can thereby create new revenue streams and at the same time reduce environmental impact. The initial step in creating an industrial symbiosis is the identification of potential substation relationships between production plants. This step is challenging, as information about the companies is often not available. Several software tools have been developed in order to identify potential symbiosis opportunities. However, these tools have the shortcoming that they require extensive data input from companies owning the production plants. This requirement limits the number of companies for which symbiosis opportunities are identified. In this paper, we propose a data-driven methodology for identifying industrial symbiosis and generating eco-industrial park architectures. The methodology is based on meta-models of industrial plants for identifying plant attributes for certain types of plants, correlations that estimate the rough amount of resource supply and demand of a plant, and a rule-based system that identifies symbiosis opportunities based on knowledge from successful symbioses. Based on the symbiosis opportunities, approach generates eco-industrial park architectures that are optimal in terms of economic and environmental performance. Finally, we apply the methodology to a case study of the existing Kalundborg eco-industrial park to evaluate if the methodology is capable of finding existing symbioses. We conclude that the methodology can be applied to screening industrial zones with standard types of industrial plants. However, the results depend on the types of existing industrial plant meta-models in the database. Future work will focus on extending the data and knowledge base; and validating the methodology by its application to other existing eco-industrial parks.

Modeling Industrial Symbiosis Using Design Structure Matrices

Today , industry is under constant pressure to increase competitiveness and resource-efficiency. One possibility to cope with these challenges is industrial symbiosis. Industrial symbiosis is based on substituting a new resource by an undervalued resource such as waste. Thereby , industrial symbiosis reduces waste and saves resources. One of the practical challenges in developing industrial symbioses is the identification of symbiosis opportunities. In particular , the question how new resource – substitute combinations can be identified has not yet been addressed in the literature. This paper presents a modeling approach for industrial symbioses in industrial parks , based on design structure matrices (DSM) , which intends to support the identification of substitution opportunities. The approach is applied to a sample industrial park. Combined with an optimization algorithm , the symbiosis model is used for identifying not only symbiosis opportunities but also the most attractive combination (s) of symbioses within the industrial park .

A Method to Design a Value Chain from Scratch

Value chain concept and methods has assumed a dominant position in studying industry from management point of view. Decision supports methods using value chain require the acquisition of data from various existing corporate databases or data warehouses. In design research discipline, the subject of value chain design is emerging. Only a few of published research took a wide scope comparable to theories used today in engineering design. As an effort in developing the methodology and as a result of research within a national industrial consortium, this paper proposes and discusses a general value chain design approach which opens up a promising perspective to provide a new direction for research and application of value chain from scratch for multi-stakeholder industrial systems. It introduces value chain design as a way to determine, model, and analyze and evaluate the industrial ecosystems, in order to generate future scenarios and provide evaluation criteria for decision makers. To illustrate its application, the establishment of end of life vehicle recycling subsidiary at national level is explored to identify potential values stakeholders.

A network flow optimization model for automotive glazing recycling

In a recycling scheme such as the recycling of End of Life Vehicle (ELV) materials, the different stakeholders are expected to configure the operation process and the product distribution to maximize their own profits. However, these individual optimizations in many cases do not correspond to the maximal profit for the whole chain. In addition, the financial autonomy must be carefully studied beforehand and controlled so as to ensure an economically viable recycling chain. This paper proposes a cost-benefit parameterized model for the ELV glazing recycling scheme both for the network structure and the material flow sizing. The model is mapped onto real ground data from French industrial partners, and a linear optimization model is built to simulate the conditions of costs and benefits situations for the upcoming glazing recycling chain in 2015 in France.Copyright