Evaluating the quality of medical care.

Digital Twin in manufacturing: A categorical literature review and classification

https://re.public.polimi.it/bitstream/11311/1049863/2/Negri%20et%20al%202017%20FAIM.pdf

A Review of the Roles of Digital Twin in CPS-based Production Systems

생체의 모델링과 Simulation

In most real-world environments, scheduling is an ongoing reactive process where the presence of a variety of unexpected disruptions is usually inevitable, and continually forces reconsideration and revision of pre-established schedules. Many of the approaches developed to solve the problem of static scheduling are often impractical in real-world environments, and the near-optimal schedules with respect to the estimated data may become obsolete when they are released to the shop floor. This paper outlines the limitations of the static approaches to scheduling in the presence of real-time information and presents a number of issues that have come up in recent years on dynamic scheduling.

The paper defines the problem of dynamic scheduling and provides a review of the state-of-the-art of currently developing research on dynamic scheduling. The principles of several dynamic scheduling techniques, namely, heuristics, meta-heuristics, multi-agent systems, and other artificial intelligence techniques are described in detail, followed by a discussion and comparison of their potential.

/pdf/a-survey-of-dynamic-scheduling-in-manufacturing-systems-1u4bc63f51.pdf

A survey of dynamic scheduling in manufacturing systems

“The most profound technologies are those that disappear… They weave themselves into the fabric of everyday life until they are indistinguishable from it” wrote computer scientist and visionary Mark Weiser nearly 25 years ago in his essay “The Computer for the 21st Century.” It turns out he was right: in the age of “Industry 4.0”, digital technologies are the core driver for the manufacturing transformation. In fact, the introduction of such technologies allows companies to find solutions capable to turn increasing complexity into opportunities for ensuring sustainable competitiveness and profitable growth. Nonetheless, the effective implementation in manufacturing still depends on the state of practice: it may slow down, or even worst, may prevent from implementation. Indeed, we assume that a minimum level of capabilities is required before implementing the digital technologies in a company. Based on this concern, our research question is “are manufacturing companies ready to go digital?”. This paper wants to illustrate a “tool” to answer this question by building a maturity assessment method to measure the digital readiness of manufacturing firms. Based on the inspiring principles of the CMMI (Capability Maturity Model Integration) framework, we propose a model to set the ground for the investigation of company digital maturity. Different dimensions are used to assess 5 areas in which manufacturing key processes can be grouped: (1) design and engineering, (2) production management, (3) quality management, (4) maintenance management and (5) logistics management. Thus, the maturity model provides a normative description of practices in each area and dimension, building a ranked order of practices (i.e. from low to high maturity). A scoring method for maturity assessment is subsequently defined, in order to identify the criticalities in implementing the digital transformation and to subsequently drive the improvement of the whole system. The method should be useful both to manufacturing companies and researchers interested in understanding the digital readiness level in the state of practice.

/pdf/a-maturity-model-for-assessing-the-digital-readiness-of-fppt3efuxn.pdf

A Maturity Model for Assessing the Digital Readiness of Manufacturing Companies

Exploring the role of Digital Twin for Asset Lifecycle Management

Despite the huge body of academic literature on inventory management of maintenance spare parts, few companies seem to deliberately use the proper approaches and tools for a factual and quantitative assessment. Detaining or not stocks of a spare item, deciding upon the right level of inventory, forecasting its sporadic consumption are just some of the evidences of the complexity and criticality underlying the daily decisions the management of a company has to undertake. The objective of the paper is to provide a stepwise decision-making path in order to orienteer an industrial manager on how to pragmatically handle the management of maintenance spare parts in a company. The framework is structured into five sequential steps: part coding, part classification, part demand forecasting, stock management policy and policy test and validation. Its applicability is demonstrated by making use of a real business case where it has been successfully adopted.

A decision-making framework for managing maintenance spare parts

https://re.public.polimi.it/bitstream/11311/1134408/1/postprint%20A%20review%20on%20characteristics%20of%20CPSs%20Napo-Macchi-Pozz.pdf

Marco Macchi

Papers

A Review of the Roles of Digital Twin in CPS-based Production Systems

A Maturity Model for Assessing the Digital Readiness of Manufacturing Companies

Exploring the role of Digital Twin for Asset Lifecycle Management

A decision-making framework for managing maintenance spare parts

A review on the characteristics of cyber-physical systems for the future smart factories