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Spreafico, Christian (2017) A new set of guidelines for inventive problem solving. [Ph.D. thesis]

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Abstract (english)

The rapid changes characterizing the economy in the last decades convinced companies, especially the most advanced, to heavily invest in innovation and in approaches to support it in a systematic way to increase the qualitative level of their products and reduce the time-to-market. Academia answered to this demand with an increasing number of publications on this topic every year; in addition, industry developed its own procedures, often internally. As result, today a lot of strategies, theories, methods and tools are available for systematic innovation. However, an accepted and unified theory and objective criteria able to assist the problem solver in the selection of the most suitable approach according to her/his needs are still missing.
The Ph.D. thesis refers to this context and its main objectives have been: (1) reviewing and classifying the huge multitude of systematic innovation methods (for new concept design, product improvement, robust design, physical investigation, information retrieval, etc.) and (2) developing a methodology to assist the designer in selecting the most suitable method in accordance with the application context.
Among the several possibilities, I choose to develop a set of guidelines that are both comprehensive and practical to apply especially in industrial contexts. However, writing guidelines is a complicated activity, as demonstrated by the numerous examples from literature describing problems and limitations in conceiving and/or applying them.
Based on literature review, involving not only papers but also patents and empirical evidences collected during the collaborations in industrial projects and tests with students, I identified the main key features of the guidelines for inventive problem solving. They are: the structure of single guideline, the organization of multiple guidelines and the suggested methods and tools. In particular, I focused attention to comprehend how the suggestions provided by the guidelines change in relation to the kinds of addressed problems, the different phases in problem solving activity and the user, and how to enrich them through specific methodological contents.
Then, according to the mentioned features, I developed a set of specific guidelines to improve Spark, a methodology for systematic innovation developed at University of Bergamo, reviewing some parts and integrating with some proposed models.
The research activities have been carried out in five phases as described in the following.
During the first activity, a state of the art about the kinds of addressed problems, and the main problem solving methods, approaches and strategies to support systematic innovation has been carried out.
In the second activity, the main features of the guidelines have been identified through a detailed analysis based on literature surveys, of Design models (e.g., FBS), Risk analysis techniques (FMEA), Problem solving tools (TRIZ) and empirical evidences collected in the companies and by involving engineering students.
The results have been organized according to three main aspects: the definition of the most suitable structure of a single guideline (in terms of provided text, graphical representations and examples), the organization of multiple guidelines (hierarchical maps, random lists, matrices, etc.) and the models and tools suggested by the guidelines in accordance to the addressed inventive problems and the phase in problem solving activity.
This results have then been summarized in a set of rules for writing guidelines.
During the third activity, the identified features have been applied to improve some parts of Spark methodology, which is structured as an ordered step by step procedure to enhance the different problem solver skills: function identification, evolutionary overview identification, problem identification, problem reformulation and idea generation. Even if this methodology has been successfully applied in industrial cases studies, it still presents some limitations (e.g., by supporting new product design).
I tried to improve Spark by expanding its domain of application to all the considered inventive problems and by ameliorating its comprehension and applicability, through an increased level of awareness of the designer while maintaining the suggested path. To do this, I improved the parts of function and problem identification through the introduction of two specific models derived from FBS and FMEA, and I reformulated the part of idea generation by providing a more rigorous ontology and a more intuitive organization to the already contained guidelines. Finally, I proposed a comprehensive set of guidelines to guide the user in the use of the improved version of Spark.
The resulting approach maintains a unique path to face all the considered inventive problems and allows specific iterations and ramifications inside the main steps, depending on the problem and the context of application.
In the fourth activity, the goal has been to drive the user to model the problem with a functional approach, in order to be able to consult the Information Retrieval tools in the proper way to find out if someone has already solved the problem in another context. More in detail, this means to conceive a guideline able to support the user in defining the right element on which to work, the function and the behaviour of the solution, at least in terms of physical effect. Patent repository is used as technical source for gathering such an information. During the doctorate, I learned techniques and software prototypes developed by the University of Bergamo, for query expansions based on hyponyms, meronyms, hypernyms and lexical variants. I tested them in industrial case studies, to comprehend how to integrate info gathering into the guidelines structure.
During the fifth activity, I recombined all the results previously achieved within of a software platform that I developed. It collects flexible guidelines, able to adapt to the different kinds of problems, which are organized through the conceptual scheme studied during the third activity, and integrates the knowledge retrieval techniques of the fourth activity.
The proposed platform and the guidelines have been tested with real industrial case studies proposed by companies with whom I collaborated, such as ABB, Tenacta-Imetec. The tests involved MsD and PhD students, during thesis works, project works and group sessions with more than 10 students each one. The achieved results, compared to traditional Spark and other approaches, have been encouraging in terms of function identification, by facilitating the determination of the required operative zone and operative time, problem identification, with an increased user’s awareness about the dynamic of occurrence, and idea generation, with a great number of qualitatively better achieved solutions.

Abstract (italian)

I rapidi cambiamenti che caratterizzano l’economia negli ultimi decenni hanno convinto le industrie, specialmente le più avanzate, ad investire ampiamente sugli approcci a supporto dell’innovazione sistematica, con l’obiettivo di migliorare il livello qualitativo dei propri prodotti e ridurre il tempo di sviluppo. L’accademia ha risposto a questa necessità con un numero di pubblicazioni in quest’ambito crescente di anno in anno; in più anche l’industria sviluppa i propri approcci, spesso internamente. Come risultato, sono oggi disponibili una grande quantità di strategie, teorie, metodi e strumenti a supporto dell’innovazione sistematica. Tuttavia una teoria unificata ed accattata è ancora mancante, così come criteri oggettivi di scelta capaci di supportare il problem solver nella scelta dell’approccio più adatto alle sue necessità.
Questa tesi di Dottorato fa riferimento a tale contesto ed i suoi principali obiettivi sono stati: (1) rivedere e classificare i molti metodi di innovazione (progettazione di nuovi prototipi, product improvement, robust design, investigazione della fisica del problema, ricerca di informazioni, ecc.) e (2) sviluppare una metodologia per assistere il problem solver nella scelta dell’approccio più adatto in relazione al contesto applicativo.
Tra le molte possibilità, ho scelto di sviluppare un insieme di linee guida che siano allo stesso tempo comprensibili e pratiche da applicare specialmente in contesti industriali. Tuttavia, scrivere linee guida è un’attività complicata, come testimoniato da numerosi esempi dalla letteratura che descrivono i problemi e le limitazioni derivanti dalla loro creazione e dalla loro applicazione.
Sulla base di una dettagliata revisione della letteratura, contenente non solo articoli ma anche brevetti ed evidenze sperimentali raccolte durante collaborazioni in progetti industriali e test con gli studenti, ho identificato le principali caratteristiche delle linee guida per la risoluzione dei problemi inventivi. Esse sono: la struttura delle singole linee guida, l’organizzazione di più linee guida ed i metodi e gli strumenti suggeriti da esse. In particolare, ho focalizzato l’attenzione per comprendere come i suggerimenti delle linee guida cambiano in relazione alla tipologia di problema affrontato, alle differenti fasi nell’attività di problem solving e all’utente, e ad arricchire le linee guida attraverso contenuti metodologici precisi.
Quindi, sulla base dei tali caratteristiche, ho sviluppato un insieme di linee guida specifiche per migliorare Spark, una metodologia a supporto dell’innovazione sistematica, sviluppata dall’Università degli Studi di Bergamo, rivedendone alcune parti ed integrandola con modelli proposti.
L’attività di ricerca è stata portata avanti in cinque fasi come descritto nel seguito.
Durante la prima attività è stato eseguito uno stato dell’arte relativo alle tipologie di problemi affrontati e ai principali metodi, approcci e strategie di problem solving a supporto dell’innovazione sistematica.
Durante la seconda attività sono state identificate le principali caratteristiche delle linee guida, attraverso un’analisi dettagliata della letteratura relativa ai modelli per la progettazione (e.g., FBS), tecniche di analisi dei rischi (e.g., FMEA), strumenti per il problem solving (TRIZ) ed evidenze empiriche raccolte nelle aziende e coinvolgendo studenti di ingegneria.
I risultati sono stati organizzati secondo tre aspetti principali: la definizione della struttura più opportuna per le singole linee guida (in termini di testo proposto, rappresentazioni grafiche ed esempi), l’organizzazione di più linee guida (mappe gerarchiche, liste casuali, matrici, ecc.) ed i modelli e gli strumenti suggeriti dalle linee guida in relazione ai problemi inventivi affrontati e alla fase nell’attività di problem solving.
Questi risultati sono stati quindi riassunti in un insieme di regole per scrivere le linee guida.
Durante la terza attività, le caratteristiche identificate delle linee guida sono state applicate per migliorare alcune parti della metodologia Spark, la quale è strutturata come un percorso ordinato e diviso in fasi per accrescere le differenti abilità del problem solver: identificazione della funzione principale, identificazione della panoramica evolutiva, identificazione del problema, riformulazione del problema e generazione di idee. Anche se questa metodologia è stata applicata con successo in casi studio industriali, presenta ancora alcune limitazioni (e.g., nel supportare la progettazione concettuale di nuovi prodotti).
Ho quindi cercato di migliorare Spark, espandendo il suo dominio di applicazione a tutti i problemi inventivi considerati e migliorando la sua comprensione e la sua applicabilità attraverso l’accrescimento del livello di consapevolezza del problem solver e mantenendo il percorso suggerito. Per far ciò, ho migliorato le parti dell’identificazione della funzione principale e del problema, introducendo due modelli specifici derivati da FBS e FMEA, e riformulando la parte della generazione delle idee con una struttura ontologica più rigorosa ed una organizzazione più intuitiva delle linee guida presenti. Infine ho proposto un insieme complessivo di linee guida per supportare l’utente durante l’utilizzo della versione modificata di Spark.
L’approccio risultate mantiene un unico percorso per affrontare tutti i problemi inventivi considerati e permette iterazioni e ramificazioni specifiche all’interno degli step principali a seconda del problema e del contesto di applicazione.
Durante la quarta attività, l’obiettivo è stato guidare l’utente a modellare il problema con un approccio funzionale, in modo da poter consultare nella maniera opportuna uno strumento per la ricerca delle informazioni, così da poter apprendere se il problema in questione sia già stato risolto in un altro contesto. Più in dettaglio, ciò significa concepire linee guida capaci di portare l’utente a definire il giusto elemento sul quale lavorare e la funzione ed il comportamento della soluzione almeno in termini di effetto fisico. I database brevettuali sono stati usati come fonte per la raccolta di tali informazioni. Durante il Dottorato, ho appreso tecniche e software prototipali, sviluppati dall’Università degli Studi di Bergamo, per espandere le chiavi di ricerca basati su iponimi, iperonimi, meronimi e varianti lessicali. Li ho quindi testati su casi studio industriali per comprendere come poter integrare il recupero delle informazioni all’interno della struttura delle linee guida.
Durante la quinta attività, ho ricombinato tutti i risultati raggiunti all’interno di una piattaforma software che ho sviluppato. Essa raccoglie linee guida flessibili, capaci di adattarsi alle differenti tipologie di problemi, organizzate attraverso lo schema concettuale studiato durante la terza attività e integra le tecniche di recupero della conoscenza della quarta attività.
La piattaforma e le linee guida proposte sono state testate con casi studio industriali reali, proposti dalle aziende con le quali ho collaborato, come ABB e Tenacta-Imetec. I test hanno coinvolto studenti della laura magistrale e del dottorato, durante lavori di tesi, progetti d’anno e sessioni di gruppo con almeno 10 partecipanti ciascuna. I risultati raggiunti, comparati con Spark tradizionale e altri approcci, sono stati incoraggianti in termini di: identificazione della funzione, facilitando l’individuazione di zone e tempi operativi, di identificazione del problema, con l’accrescimento della consapevolezza relativa alla dinamica di accadimento e di generazione delle idee, con un maggior numero di soluzioni qualitativamente migliori identificate.

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EPrint type:Ph.D. thesis
Tutor:Savio, Enrico
Supervisor:Rizzi, Caterina and Russo, Davide
Ph.D. course:Ciclo 29 > Corsi 29 > INGEGNERIA INDUSTRIALE
Data di deposito della tesi:13 January 2017
Anno di Pubblicazione:13 January 2017
Key Words:Innovazione Sistematica, Linee guida Inventive per la soluzione inventiva dei problemi, Computer Aided Innovation, Systematic Innovation, Guidelines for Inventive Problem Solving, Computer Aided Innovation
Settori scientifico-disciplinari MIUR:Area 09 - Ingegneria industriale e dell'informazione > ING-IND/15 Disegno e metodi dell'ingegneria industriale
Struttura di riferimento:Dipartimenti > Dipartimento di Ingegneria Industriale
Codice ID:9835
Depositato il:02 Nov 2017 15:32
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