**2. Literature review**

The literature review of this paper aims to democratize and centralize the main concepts and new technologies used in the development of the project. Industry 4.0 concepts have been presented through Cyber-Physical Systems, IoTs, big data analytics, Artificial Intelligence (AI). With the focus on studying logistics within hospitals, research was conducted in the fields of Logistics 4.0 and Healthcare 4.0 to connect the two concepts. Finally, research was carried out into the methods used to optimize processes such as Lean Manufacturing and Lean Healthcare. Hence the chapter has a summary of each of the topics that were necessary to develop the tool and concepts presented in this article.

#### **2.1 Industry 4.0**

Based on some values and known as the fourth industrial revolution (**Figure 1**), industry 4.0 is a term that emerged in Germany in the 2011 edition of the Hanover Fair, seen as a tech strategy for 2020, and remarkably based on the development of cyber systems. Modern industrial systems are complex systems that include physical, software, and networking elements into so-called cyber-physical systems [1].

Cyber-physical systems are considered as the heart and the base of the 4.0 industry [2]. The Internet of things and the Internet of services, allow to define "intelligent manufacturing", which together with the production planning and control should play a key role within the 4.0 Industry [3, 4]. By using the Internet, Industry 4.0 matches products, services, production, and optimization to build a process based on data recorded by cyber-physical systems, without the need to involve a human being [3].

The context of Industry 4.0 is influenced by the intelligent capabilities of five basic technologies (Internet of Things, Cyber-physical Systems, Big Data and Analytics, Artificial Intelligence, and Additive Manufacturing), which have greatly stimulated the development of intelligent manufacturing [2, 4]. As a preferred

#### **Figure 1.**

*Four industrial revolutions.*

means of such integration, Cyber-physical systems, and digital twins (DT) have gained great attention from researchers and industry professionals [2]. Indeed, robot, cobot, mobile robot, intelligent machines, immersive realities, IoTs represent machines and tools that could increase the efficiency of the industry4.0 concepts.

Artificial intelligence (AI) methods and tools such as expert systems, machine learning, deep learning, multi-agent systems are used for supporting Industry 4.0 concepts implementation in the company digital transformation through modeling, simulation, or decision support systems. These methods are also used for the same reasons in the frame of healthcare. For instance, Case-based reasoning (CBR) and multi-agent systems concepts are exploited in [5] for predicting risk in surgery in a non-determinist context. Case-based reasoning process is described as a cycle of four processes: Retrieve the most similar cases, Reuse the cases for solving a new problem, Revise the proposed solution, and Retain the new solution as a new case [6, 7]. This cycle is generally used in medical classification, prediction, and diagnosis problems. These concepts are adapted to hospital processes transformation and could be combined with multi-agent systems (MAS). MAS are defined as a composition of autonomous entities that interact with to certain rules in a specific environment. For instance, MAS could be used for solving problems such as the ecological and epidemiological analysis of infectious diseases [8]. In this kind of combination MAS could generate risk situation that will be compared to old cases by the CBR system for solving problems [5]. This hybrid system philosophy is also adapted for solving hospital logistics flow problems. Indeed, a decision aided system that will measure the state of healthcare logistics digital transformation could be elaborated by using expert systems theory and architecture. As described in [9], expert systems are used for supporting different application domains such as ontologies elaborated for modeling and managing the knowledge about drugs and patients [10] which flows (in this paper case) must be optimized in healthcare logistics.

#### **2.2 Logistics 4.0**

Logistics 4.0 is a relatively new term, directly linked to Industry 4.0. The development of Industry 4.0 was based on digitalization and automation, and that for Logistics 4.0 presents not only enormous challenges but also opportunities to increase efficiency [11]. Indeed, before the advent of Industry 4.0, the concept of intelligent logistics was previously introduced to represent a technology-driven approach to the management of material flows within and outside the factory limits [12]. The concept of Logistics 4.0 means a set of solutions aimed at improving logistics processes, avoiding errors and disruptions in transport and storage processes, thanks to the continuous exchange of data between the players in the logistics system [13].

Logistics 4.0 is a combination of technical and organizational solutions aimed at improving material and information flows and adjusting them to meet the requirements of Industry 4.0 solutions. Therefore, logistics is intended to support manufacturing processes, whereby, as they evolve towards intelligent and autonomous solutions, logistics must follow this change [13].

Due to the fact that the Industry 4.0 concept is considerably affected by the use of new technologies, logistics 4.0 has been intuitively perceived from the perspective of technological achievements and applications (e.g. GPS, WMS, TMS, RFID, CPFR, etc.) [14]. In addition to the explanations mentioned above, modern companies make use of dedicated technologies such as goggles, gates, forklifts, and automatic vehicles, or even intelligent carriers. The objective of this concept is to increase the efficiency and performance of the members of the supply chain [15].

It has been assumed that the new technologies and tools are determining factors for the realization of Logistics 4.0 and that they can be used as evaluation criteria for the implementation level [14]. Through the implementation of Logistics 4.0, many advantages can be noted, among them the lower cost in human work, the high standardization in logistics functions, and the use of new technologies in the equipment of logistics companies. The disadvantages are the high investment costs and the requirement to own the information technology supply network [15]. These concepts could be used in healthcare logistics for optimizing flows but also respecting Covid pandemic distancing attitudes and saving lives.

#### **2.3 Healthcare 4.0**

Healthcare industry has been assisting in saving and extending patients' lives through the progress of technologies adopted by healthcare professionals and through the transformations that the sector has undergone. In the health field, the practices and techniques have been developed from Healthcare 1.0 to Healthcare 4.0. In the context of Healthcare 1.0, there was a scarcity of resources and the efforts were primary since the approach was doctor centric. As the information technology field and medical technologies advanced, it was possible to replace manual records with electronic healthcare records (EHR), what has been termed Healthcare 2.0. Healthcare 3.0 had, as the main characteristic of the patient-centric approach, developed new and effective treatment methods through data processing systems and computational methods. In this context, EHR was used to help doctors to get important information faster. Healthcare 4.0 corresponds to the integration of new technologies, such as Cloud Computing, Internet of Things, Fog Computing and Telehealthcare, to facilitate the doctor-patient interface through data portability. Strong communication interface and the ability to share data enable doctors to make well-informed decisions and increase the quality of healthcare around the world [16, 17].

The adoption of Industry 4.0 main technologies, such as the Internet of Things, Cloud and Fog Computing, and Big Data analytics, has revolutionized the healthcare sector, changing the way to provide traditional products and services. IoT is supposed to integrate the virtual and physical world through interconnected devices and platforms. The Internet of Health Things (IoHT) has as main objective,

#### *How to Improve Hospital Flows in the Context of the COVID Pandemic DOI: http://dx.doi.org/10.5772/intechopen.98672*

the tracking of patient medical conditions and the anticipation of critical situations through the combination of connected devices. The Internet of Medical Things aims to create a personal hub connecting implantable and wearable devices to a personal smartphone. Cloud, Fog and Mobile Edge Computing represent a huge part of Healthcare 4.0 to simplify health processes, facilitate the adoption of healthcare best practices, and inspire the adoption of more innovations. The healthcare sector can benefit from the capacity of management of a huge amount of data demonstrated by Cloud and Fog Computing. Big data and analytics are largely used in the healthcare sector, not only to store and treat patient data but also to collect enterprise data, allowing to implement studies that cover beyond the health domain (biological and medical aspects) [18] and to analyze them in detail for taking good decisions and aiding doctors in the patient support.

The implementation of Industry 4.0 core principles in the healthcare sector is far from optimal, despite the great importance of its main technologies isolated. The problem lies in the fact that a successful implementation of Healthcare 4.0 implies transformations of technical and sociocultural aspects inside the hospitals. The main barriers are associated with the development of an incorporated IT infrastructure aligned with the hospital's strategy. This issue is proven that healthcare has been the slowest sector to adopt information technologies. To mitigate this problem, the focus must change from design and implementation processes to the end-user experience with solutions already implemented, i.e., more prototypes must be tested [19, 20]. Indeed, this transformation has to be linked with the global healthcare logistics organization.

### **2.4 Lean manufacturing and lean healthcare**

In recent times, the enterprise environment requires the implementation of the Lean Manufacturing approach to create added value with optimal resource utilization. Aiming to present the Toyota Work Philosophy, the term 'Lean' first appeared in the 90s. The bases of this philosophy are waste elimination and value creation. Waste can be defined as all processes that do not create any added value. Seven types of Mudas (tasks with no added value) were developed: overproduction, wait, transport, stock, unnecessary activity, defects, and motion. The overproduction is the task that generates the most losses [21].

To implement the Lean philosophy, several tools and techniques were developed to reduce/eliminate waste. The use of the tool VSM (Value Stream Mapping) enables the decision making of the Lean through the analysis of a deterministic and static value chain observation. VSM helps to distinguish the non-waste and waste processes [22]. The implementation of the Lean Manufacturing approach is realized in three main stages: pre-implementation stage (lean readiness), implementation stage (lean approach), and post-implementation stage (results) [23].

Aiming at increasing process efficiency and mitigating non-added value processes, Lean Manufacturing methods have been extensively implemented in healthcare institutions [24]. The main uses of Lean in this context are to eliminate duplicate and unnecessary procedures, such as collecting patient information several times, unnecessary patient displacement, excessive waiting by patients for appointments, and uncoordinated processes. Despite the wide application of lean assumptions in hospitals and clinics, the prospected results are not achieved [23]. The significant number of failures can be explained by 3 main factors:

• Absence of adaptation: it is essential to adapt lean concepts to knowledgeintensive service sectors such as healthcare. This transition is not always clear, which causes a higher probability of failures [23].


With this purpose and to help the production process in SMEs (Small and Medium Enterprises), a methodology and a framework has been developed with the aim of contributing to the implementation process of industry 4.0 and logistics 4.0, with the focus on sustainability aspects [4, 24]. The next section presents concepts and methodology that could firstly be used for transforming digitally the hospitals and increasing their flow performance, and secondly be integrated in the process of both patient and hospital staff lives saving in the context of covid pandemic.
