Post-Series Design: a tool for catalysing the diffusion of personalisable design.

Today a range of increasingly mainstream Digital Fabrication tools help designers not only in prototyping, but also in the production of final parts for consumer products. These hardware tools, while still have significant limitations, they already offer new levels of morphological freedom and logistical flexibility, which allows the efficient production of personalisable products – supposing advanced software tools of Parametric Design. However, since DF, PD and personalisation are still marginal, one may suspect that the Design profession has a shortage of adequate capabilities. Therefore, this contribution proposes a conceptual tool focused on valorising the previous hardware and software tools to achieve meaningfully personalisable products. The proposed canvas tool is structured specifically to facilitate opportunity identification and conceptual design, based on a set of key advantages (variabilities) derived from numerous case studies of existing personalisable products realised with DF. The new approach and tool have been experimented with a class of product design students, but it also aims to facilitate product development at enterprises, coherently with the emerging Industry 4.0 paradigm

An overview of decision table literature 1982-1995.

This report gives an overview of the literature on decision tables over the past 15 years. As much as possible, for each reference, an author supplied abstract, a number of keywords and a classification are provided. In some cases own comments are added. The purpose of these comments is to show where, how and why decision tables are used. The literature is classified according to application area, theoretical versus practical character, year of publication, country or origin (not necessarily country of publication) and the language of the document. After a description of the scope of the interview, classification results and the classification by topic are presented. The main body of the paper is the ordered list of publications with abstract, classification and comments.

Risk Mitigation and Monitoring Challenges in Software Organizations: A Morphological Analysis

Context: The present body of research on risk mitigation focuses mostly on sparse and dispersed research using various approaches during project development. Objectives: This paper's goals are to conceptualize and construct a morphological analysis (MA) framework, examine the literature that has already been published on these risks and how to mitigate them in software development, and identify research gaps that suggest areas for further study. Methods: Based on a survey of 102 works, we provide an MA framework. The MA framework, which is composed of five dimensions and 17 variants, identifies 33 distinct research gaps as the maximum number of potential areas for future study. The implications for future research are covered in the paper's conclusion. Risk reduction during the project development process is extremely beneficial for project managers at an organization in delivering high-quality goods on time and within budget. Results:  Based on a review of the literature, it was discovered that the development of software projects used a very low percentage of official risk mitigation and elimination methods. Research also revealed the significance of people-related risks in the risk mitigation process for the benefit of the organization. Some key research demonstrated experimentation, case studies, and empirical approaches for evaluation. Future work may include examining project managers' perceptions and knowledge of risk management. Managers of software development teams require greater risk-mitigation strategies. Conclusion: Scholars and researchers need to put more effort into developing quantitative and intelligent risk models. It is crucial to identify major risks so that they won't compromise the project's future success. In our future work, we can employ more models that are helpful for combining quantitative and intelligent risk models using various AI strategies to reduce hazards

The Role of Knowledge Management in Supply Chain Management: A Literature Review

Purpose: The aim of this paper is to examine the state of knowledge management research in supply chain management from three standpoints, methodological approach, supply chain management area, and knowledge management processes. Design/methodology/approach: To achieve this, a systematic review is conducted over the period 2000-2014 on the basis of a qualitative content analysis. Findings: Major results showed that knowledge management can be viewed as a leverage mechanism for: (i) supply chain integration; (ii) the enhancement of intra and inter-relations across the supply chain; (iii) supply chain strategy alignment; and (iv) the reinforcement of knowledge transfer in product development. Some supply chain management areas such as reverse logistics, inventory management, forecasting/demand planning, outsourcing, and risk management have been explored only to some extent. Furthermore, knowledge transfer is being studied in the majority of the articles, mainly by both case study and survey approach; mathematical models and simulation techniques are used in very limited articles. Findings concerning theoretical perspectives and managerial issues are also described. Research limitations/implications: The limitation of our study encompasses the aspects of search period (2000-2014), selection of search databases (Web of Science and SCOPUS and language selection (English). Practical implications: The exhibition of the KM processes within the SC context may help practitioners and managers interested in implementing KM initiatives to replicate the methodologies in order to increase the possibilities of a successful KM adoption. Originality/value: The systematic review will contribute to the understanding of the present state of research in the knowledge management theory, with focus on the supply chain, as there are no state-of-knowledge studies that report a systematic literature review approach.Peer Reviewe

Landslide Risk Assessment by Using a New Combination Model Based on a Fuzzy Inference System Method

Landslides are one of the most dangerous phenomena that pose widespread damage to property and human lives. Over the recent decades, a large number of models have been developed for landslide risk assessment to prevent the natural hazards. These models provide a systematic approach to assess the risk value of a typical landslide. However, often models only utilize the numerical data to formulate a problem of landslide risk assessment and neglect the valuable information provided by experts’ opinion. This leads to an inherent uncertainty in the process of modelling. On the other hand, fuzzy inference systems are among the most powerful techniques in handling the inherent uncertainty. This paper develops a powerful model based on fuzzy inference system that uses both numerical data and subjective information to formulate the landslide risk more reliable and accurate. The results show that the proposed model is capable of assessing the landslide risk index. Likewise, the performance of the proposed model is better in comparison with that of the conventional techniques