**2. Materials and Methods**

Section 3.1 is a review of the literature that shows the historical development of SCIMs, focusing on the main technological innovations, material improvements, and various projects. The sources of information are technical documents from SCIM manufacturers or scientific articles that described the processes and the main events that caused the changes in the mass/power ratio between 1890 and 1990, contributing to answering question I.

In Section 3.2, a literature review is presented discussing the variations in performance between 1935 and 2012, contributing to answering questions I and II.

In Section 3.3, the primary data collected in the Technical Test Reports of the Laboratory of Electrical Machines of the Institute of Energy and Environment (IEE) of the University of São Paulo (USP) are presented and discussed.

Between 1945 and 1996, the Technical Test Reports were only available in printed form. Thus, it was necessary to digitize the data and collect them into a spreadsheet. Between 1997 and 2020, the Technical Test Reports were already available in digital format for processing and analysis.

The Laboratory of Electrical Machines of the IEE-USP has a technical collection of approximately 21,000 technical reports. For this analysis, reports with the following characteristics were considered:

Using the conditions expressed in a–g, 359 technical reports of tested SCIMs with speeds corresponding to 2, 4, 6, or 8 poles, with a motor rated output power of 3.7, 37, or 150 kW, were collected for the evaluation of the change in performance between 1945 and 2020. The assessment seeks to answer the questions (I and II) that motivated this research, based on the data collected.

The results are organized into three different output power (kW) categories. The chosen groups include low power (3.7 kW), medium power (37 kW), and high power (150 kW). As the groups chosen to represent SCIMs are of significantly different dimensions, the production processes used in the manufacturing process and the standards of precision/quality of the materials are also different, even when dealing with the same equipment.

The number of poles of the electric motor determines the rotation speed, due to the arrangement and distribution of the electrical conductors of the windings located in the stator slots. In the SCIM market, historically, four speeds have been the most used. Between 80% and 90% of all the SCIMs sold have between 2 and 8 poles; therefore, this research evaluates them in this speed range. In fact, 4-pole SCIMs are dominant, representing between 45 and 70% of SCIMs [21,47].

Using the conditions expressed in a–g, 28 SCIMs with speeds corresponding to 2 poles and motor rated output powers of 3.7, and 4.4 kW were used to evaluate the change in the mass/power ratio between 2000 and 2020, seeking to answer the questions (I and III) that motivated this research, based on the data collected.

The National Institute of Metrology, Quality and Technology (INMETRO) accredits the Laboratory of Electrical Machines at IEE-USP, following ABNT NBR ISO/IEC 17025:2017 [48] under No. CRL 0011. INMETRO periodically carries out audits in accredited laboratories, aiming to guarantee the quality of the measurement results. INMETRO is a signatory to the mutual recognition agreements of the International Laboratory Accreditation Cooperation (ILAC) and the Inter-American Accreditation Cooperation (IAAC), thus following a world standard of quality and reliability.

This research, therefore, used data from standardized performance tests. This is because there may be differences between values measured in neutral laboratories and values reported by manufacturers [49], and when using the measured data, errors and uncertainties are reduced.

#### **3. Results and Discussion**

#### *3.1. The Improvements in SCIMs*

All the technological and theoretical bases for electric motor development were already advanced by the end of the 19th century. Direct-current motors were on the market, and alternating-current motors were in the full developmental stage, with research ongoing in Europe and the United States. The first patent for the electric motor with asynchronous technology was filed by the engineer Nikola Tesla [50] in 1888 and accepted in 1889 [51] in New York. The asynchronous motor became known as an induction motor, based on its working principle. However, Tesla's proposal was similar to the current single-phase auxiliary winding motors, operating with a wound rotor. The text that explained the working principle of the new electric induction motor was published by Nikola Tesla in 1988 with the title "A new system of alternate current motors and transformers" [52].

Parallel to Nikola Tesla's experiments in the USA were those of Galileo Ferraris in Italy. In 1885, Ferraris developed the idea that two out-of-phase currents could be used to produce two magnetic fields that could be combined to produce a rotating field, without the need for switching or moving parts, opening the door to AC electric motors [53–55].

The three-phase squirrel-cage rotor induction motor (SCIM) closest to the type we have today was developed by a German company AEG (Allgemeine Elektricitäts-Gesellschaft), headed by the Russian engineer Mikhail Dolivo-Dobrovolsky between 1888 and 1890 [56]. The electric motor developed by the Dobrovolsky team had very favourable characteristics such as high starting torque, more straightforward construction features, robustness in construction, and low maintenance needs. However, it also had the inconvenience of needing to be powered by a three-phase alternating-current system, which was not yet commercial. Until then, the available electrical systems were single-phase and two-phase systems. This type of supply does not provide efficient starting of the Tesla-mounted motor (starting torque practically non-existent), in addition to imposing some degree of vibration during operation. The SCIM has a high starting torque and does not need auxiliary windings and accessories such as a capacitor and a centrifugal starter, in addition to having a lower operating current compared to a single-phase motor. However, three-phase electric power generation, transmission, and distribution systems were quickly implemented with the objective of feeding the attractive SCIMs [57–59].

Dobrovolsky and the AEG company gained fame for the great invention. The artist Irene Ahrens created the illustration in Figure 3, which was exhibited in Berlin. The engineer appears in the sky, entering the Hall of Fame with his SCIM shown near his feet.

**Figure 3.** Mikhail Dolivo-Dobrovolsky entering the Hall of Fame with his SCIM. Source: [57,60].

In 1891, at AEG, Dobrovolsky coordinated the first serial production of SCIMs with shaft powers between 0.4 and 7.5 kW. The first SCIMs assembled had a performance of approximately 80% for the power range produced and very high mass by today's standards. The first commercial two-pole SCIM with a shaft power of 4.4 kW was marketed in 1891. These SCIMs had a mass/power ratio of 86 kg/kW, as shown in Figure 4.

**Figure 4.** Improvements in SCIM mass/power ratio between 1891 and 1984. Source: [61–63].

The company AEG published the famous image represented in Figure 4, which shows the mass/power ratio from the first SCIMs manufactured by the company in 1891 to the SCIMs manufactured in 1984. The optimization of materials for electrical, magnetic, and mechanical purposes, combined with solid technological innovations, made it possible to reach a ratio of 6.8 kg/kW in 1984, representing only 8% of the total mass of the two-pole SCIMs with an axle power of 4.4 kW produced in 1891, as AEG's first commercial units.

The concept of the SCIM has not changed since the beginning of its commercialization; however, the volume has changed considerably (Figure 4).

The technological progress of SCIMs has been remarkable, stimulated by strong competition and by processes, technological innovations, and improvements in materials. According to Browning (1997) [64], the changes in the mass/power ratio resulted in better operational characteristics, even more excellent reliability, versatility, and longer life.

Browning (1997) [64] identified the following improvements in SCIMs:

The adoption of industry standards has played a significant role in the progress of SCIMs [28,64]. An example is the thermal classification of insulating materials, which first appeared in 1898. In 1911, standardization by the AIEE Standards (now IEEE—Institute of Electrical and Electronics Engineers) established temperature limits for SCIMs. The 1915 edition of the AIEE Standards included definitions of insulation classes A, B, and C and the materials assigned to those classes. In 1929, the first SCIMs built to NEMA standards were made available on the market, setting standard dimensions and operating characteristics for specific ratings for the first time. Users were given the ability to directly replace SCIMs via the concept of stock electric motors for quick replacement in case of failure [64].

It is possible to observe in Figure 5 the tremendous technological innovations that were decisive in reducing the mass and volume of SCIMs.

**Figure 5.** Chronology of 0.75 kW SCIM mass reduction between 1900 and 1990. Source: [65–68].

At the beginning of the 20th century, the first major technological innovation was the development of ball bearings, replacing the traditional plain bearings that were bulky, heavy, and required lubrication with oil. With the new bearings and the reduction in friction losses, the mass and volume of the SCIMs decreased considerably.

Between 1913 and 1940, there were gains in the quality of materials, improving compaction and making it possible to reduce the volume of copper and iron used in SCIMs and to reduce losses. In the 1940s, rotors previously built using iron sheets began to be developed using cast aluminium, adding more mass reduction, as shown in Figure 5. In addition, in the 1940s, with successive advances in metallurgy, SCIM housings could be built in an increasingly closed way and could maintain the cooling of the windings located in the stator.

In the early 1960s, a series of advances in insulation systems were instrumental in reducing the volume of SCIMs. Between 1960 and 1970, SCIMs went through five generations of materials used to construct insulation for electrical conductors. In the first SCIMs, the insulation was composed of paper, and later cotton. Then, insulation with varnish predominated until the present day. Figure 6 shows in white the area necessary to accommodate electrical conductors of the same metallic volume inside the stator magnetic package slot for different insulation technologies [63].

The first significant innovation in SCIM insulation systems was the replacement of the double layers of cotton between the conductors and the sheets with two layers of silk, allowing a reduction of approximately 59% of the groove area in the metal sheets (ferromagnetic material) of the stator. The second major innovation was the introduction of varnish used in conjunction with silk, giving an area reduction of over 2%, as shown in Figure 6. Subsequently, improvements in the quality of silk and varnish allowed an area equivalent to be reached of only 22% of the space required for the same electrical conductor using cotton as an insulator.

**Figure 6.** Space used by different insulation technologies for the same SCIM output power. Source: adapted from [63].

Successive technological innovations and improvements in electrical, magnetic, and mechanical materials achieved significant volume compaction in SCIMs between 1903 and 1974 [28], as illustrated in Figure 7a. Figure 7b shows the changes in appearance and frame dimensions of SCIMs of different powers from the open construction of 1904 to those used in the 1970s, similar to today's drip-proof and fully fan-cooled SCIMs.

**Figure 7.** Dimension trends and housing changes of 11 kW 4-pole SCIMs between 1903 and 1974. (**a**,**b**): the changes in appearance and frame dimensions of SCIMs of different powers from the open construction of 1904 to those used in the 1970s. Source adapted from: [28,53].

Figure 7a presents SCIMs designed for operation at 220 volts and 11 kW, built by General Electric (GE). In Figure 7a, it is possible to observe the changes in the NEMA 404 housing over the years, and two significant innovations are evident in the images of SCIMs between the years 1920 and 1954: axial extension of the rotor at the rear and the closed housing, seen from 1954 and made possible by the improvement in insulation systems, enabling the transfer of heat from the windings to the outside.

Figure 7b shows a small SCIM (1904) built without a fan and considered to be "selfventilated" by the semi-open housing. As early as 1918, SCIMs used a fan attached to the shaft for cooling. In 1930, the 15 kW SCIM already had a more efficient fan and could

adopt a more closed design. In 1972, the engines were already drip-proof. Figure 7b shows 18.5 kW and 45 kW SCIMs. They could be fully enclosed (45 kW), allowing a reduction in SCIM dimensions. As a result of the improved insulation between the conductors and between the conductors and the ferromagnetic material of the sheets, the temperature of the winding wires and the groove walls became more homogeneous, as they were closer together with a thinner insulating layer. The temperature of the set decreased, and for this reason it was possible to increase the power considerably for the same housing. The stator slot was significantly reduced for the same power, and the magnetic section between the slots could be increased. There was also an improvement in the ferromagnetic material, an increase in the magnetic flux, and a consequent decrease in the number of turns per stator coil for the same electrical voltage.

According to Alger and Arnold (1979) [28], to avoid hot spots in the centres of long cores, radial ducts were introduced in the stator and impellers in the rotor operating as fans, creating the airflow through the stator channels. Therefore, the rating given to the NEMA 404 frame with an axle height and length of 25.4 cm and 31.1 cm, respectively, was increased with respect to mechanical power from 5.5 kW in 1897 to 75 kW in 1974, as shown in Table 2.

**Table 2.** Mechanical power increments in the same frame from 1898 to 1974. Source: [28].

The reduction in the volume of SCIMs also made it possible to reduce their costs, intensifying the electrification of industrial plants. For example, in 1890, a 3.7 kW SCIM weighed approximately 450 kg and cost about USD 900, and in 1957, a SCIM of the same power weighed around 50 kg and cost USD 110 [64]. Thus, the relationship between value and mass remained practically the same. However, as mass reduced significantly, the price of the SCIM reduced considerably, since the cost of an SCIM is fundamentally a function of the quantity and quality of materials used.

The company Hitachi produced three SCIMs of 3.7 kW in 1910, and in 2010 the total production was already 40 million SCIMs. The company recorded the significant advances that SCIMs have made over more than 100 years in this period. Hitachi divides advances in electric motors into three distinct periods. Between 1830 and 1890 is the period of inventions, from 1930 to approximately 1950 is the period of scientific initiatives, and between the 1950s and the present day is the period of industrial initiatives [69].

Various technical and technological developments have made Hitachi SCIMs smaller and lighter over the 100 years from 1910 to 2010. Figure 8 presents the leading technologies used by Hitachi that made it possible to reduce the mass of the first SCIM, with a power of 3.7 kW (four poles) manufactured by the company in 1910 with a mass of 150 kg, to approximately 20% of the mass in 2010 (30 kg).

**Figure 8.** Hitachi SCIM mass changes for 3.7 kW (4 poles) SCIMs. Adapted from [69].

The main changes recorded were the use of aluminium in the rotor in the late 1940s. Later, in the 1950s, bearings improved, moving from sliding technology to ball bearings. In the late 1960s, improvements were made with the application of new insulation classes of varnishes on the wires. In the mid-1970s, cast iron frames gave way to lighter sheet steel frames. In the 1990s, aluminium structures closed the cycle of major technological innovations in Hitachi's first 100 years (1910–2010).

Reduction of Volume and Losses of Ferromagnetic Materials in SCIMs

The first electrical devices to use ferromagnetic materials were developed in the second half of the 19th century. Knowledge about these materials, such as their structure, was absent; as a result, the development of the projects was based on trial and error [70].

For SCIMs to thrive, they needed to advance in generating, transmitting, and distributing electrical energy via alternating current (AC) [71]. Charles Proteus Steinmetz was hired by General Electric (GE) (by Thomas Alva Edison) to improve the AC distribution system. He developed the complex representation of variables sinusoidally in time, which is still in use today [72]. Steinmetz deepened his studies of ferromagnetic materials to better compete with Westinghouse, which manufactured the induction motors invented by Tesla.

The first concepts regarding losses in ferromagnetic materials, traditionally known as iron losses, were developed by Steinmetz [73]. Via understanding how the losses behaved with changes in the intensity of the magnetic field, the General Electric induction motors became competitive, due to the reduction in the volume of material used [74].

Steinmetz's secret was to use increasingly thin sheets. The eddy current losses depend on the square of the sheet thickness, the hysteresis losses, and the square of the magnetic field strength [75]. Steinmetz's discoveries led to more efficient rolling mills that produced thinner and thinner sheets.

Understanding the ferromagnetic losses (hysteresis and eddy current) was decisive for selecting increasingly thin sheets to assemble the stator and rotor magnetic package. Thus, it was possible to impose a greater magnetic flux density in the package of sheets, approaching the limit of the magnetic saturation of the plate. This knowledge contributed to reducing the volume of SCIMs to approximately one third of the initial volume between 1891 and 1901 (Figure 4).

Subsequently, the development of ferromagnetic materials focused on reducing iron losses through heat treatment of the materials and the "doping" of silicon to increase the resistivity of the composite [76], thus enabling the intensification of the magnetic field and consequently reducing the volume of the SCIMs for a defined power.

To better understand the reason for the volume reduction of SCIMs over time, as shown in Figure 4, regarding the reduction provided by the improvement in ferromagnetic materials, it is possible to model the volume of SCIMs from the increase in the intensity of the magnetic field in their structures. This imposition of increasingly intense magnetic fields was one of the main reasons for the reduction in the volume of electric motors since their development.

A mathematical expression that translates the volume/power ratio as a function of the imposed magnetic flux density can be deduced from the electromechanical energy conversion equation, where the phase-induced electromotive force is given by Cardoso et al. [70]:

$$\mathbf{E} = \mathbf{4.44fN}\_{\text{eff}} \boldsymbol{\mathcal{Q}} \tag{1}$$

where f is the frequency (Hz), Neff is the number of adequate turns in series per phase, and ∅ is the magnetic flux per pole (Wb).

Furthermore:

$$\mathcal{Q} = 2 \frac{\text{BLR}}{\text{P}} \tag{2}$$

where B is the density of the magnetic flux in the air gap (T), L is the packet length (m), R is the radius of the air gap (m), and p is the number of pole pairs.

The electric current expressed as a function of the magnetic field in the motor air gap was expanded from the classical magnetomotive force equation FMM = NI = φ, and can be expressed as [70]:

$$\mathbf{I} = \frac{\pi \mathbf{p} \mathbf{l}\_{\mathbf{g}} \mathbf{B}}{3\sqrt{2}\mu\_0 \mathbf{N}\_{\mathbf{eff}}} \tag{3}$$

where μ<sup>0</sup> is the magnetic air permeability (H/m), p is the number of pole pairs, and lg is the thickness of the air gap (m).

Ignoring any type of losses, the motor power will be given by P = mEI, where m is the number of motor phases.

Substituting E and I by their values expressed in Equations (1) and (3) results in:

$$\mathbf{P} = \frac{\pi \mathbf{m} \mathbf{p}^2 \mathbf{l}\_{\mathfrak{E}} \mathbf{n}}{3\mu\_0} \mathbf{B}^2 \text{Vol} \tag{4}$$

where n = <sup>f</sup> <sup>p</sup> represents the synchronous motor rotation in rps and Vol <sup>=</sup> <sup>π</sup>R2L represents the motor volume.

Reorganizing Equation (4), it is possible to mathematically verify the volume/power ratio of SCIMs and other equipment that uses ferromagnetic materials, in proportion to the intensity of the internal magnetic field in Equation (5).

$$\frac{\text{Vol}}{\text{P}} = \frac{1}{\text{K}\_{\text{m}}\text{B}^{2}}\tag{5}$$

with:

$$\mathbf{K}\_{\mathbf{m}} = \frac{\pi \mathbf{m} \mathbf{p}^2 \mathbf{l}\_{\mathbf{g}} \mathbf{n}}{3\mu\_0} \tag{6}$$

Equation (5) is inversely proportional to the magnetic flux density characteristic square, expressing a curve similar to that of Figure 4. It suggests that one of the primary explanations for the reduction in the volume (or mass) of SCIMs over the years was the

more significant imposition of the magnetic field on its magnetic structure, as shown in Figure 9.

**Figure 9.** Density of the magnetic flux in the air gap and the volume of SCIMs.

Figure 9 represents the relationship between the improvement in the quality of the ferromagnetic material and the reduction in SCIM volume, considering the same output power. As a result of Equation (5), the curve is theoretical since it is impossible to design an electric machine with unlimited magnetic flux density (B) or a value of B very close to zero. Hence, the curve represents one of the essential reasons for the reduction in the volume of SCIMs from the first units to the present day.

It is estimated that for 110 kW electric motors, the losses in ferromagnetic materials represent, on average, 59% of the total losses [77]. The losses increase with increasing frequency of the electric voltage. These materials have also undergone improvements from the first electric motors to the current ones.

Since Michael Faraday demonstrated electromagnetic induction in 1831 [78], soft magnetic (ferromagnetic) materials have continued to evolve. When iron was the only soft magnetic material available, metallurgists and materials scientists experimented by introducing other elements to improve the efficiency of iron.

The main known losses in ferromagnetic materials are hysteresis and eddy current losses. Hysteresis losses occur through the coercivity of a magnetic material. Each time a material with magnetic characteristics completes an entire cycle of its magnetization curve, the area within this curve measures the energy lost in the magnetization process.

The second primary loss mechanism in soft magnetic materials is eddy currents. Eddy currents are closed electric current paths generated in a conductor whose source is a timevarying magnetic field. These current loops create a magnetic field in opposition to the change in magnetic flux (according to Faraday's law of induction). The energy losses caused by eddy currents scale approximately with the square of the operating frequency and are thus a significant cause of losses in alternating-current machines.

The development of silicon (electrical) steel in about 1900 was a notable event in the advances of soft magnetic materials [79]. Silicon steel still dominates the global soft magnet market and is the material of choice for large-scale transformers and electrical machines such as SCIMs. In 1900, Robert Hadfield, a metallurgist from England, and his team developed unoriented silicon steel by adding up to 3% of silicon to iron and increasing its electrical resistivity (ρ) [80].

The team led by the American metallurgist Norman Goss developed grain-oriented silicon steel in 1933, promoting grain growth along a crystalline direction. The most common applications for silicon steel are large-scale transformers (grain-oriented silicon steel) and electrical machines (unoriented isotropic silicon steel is preferred for rotating machines), for which the economical price is a great benefit [80].

Improvements in magnetic properties were also achieved, from the treatment of iron to minimize chemical impurities to the techniques of slicing the iron into thin sheets. Subsequently, silicon was used to increase the electrical resistance of iron and control the crystal orientation. Figure 10 presents the reduction in losses in the core of electrical machines in watts for each kilogram of ferromagnetic material, highlighting the predominant technological advances of each period.

**Figure 10.** Changes in losses in the core of electrical machines (ferromagnetic material). Source: adapted from [7,76,81].

It is possible to observe in Figure 10 that between 1884 and 1970, the losses in the core of alternating-current electrical equipment reduced from 8.16 W/kg to 0.44 W/kg, which represents an approximately 95% reduction.

Figure 10 shows low frequencies (50 or 60 Hz) and a constant B (T) value, as both directly influence losses in ferromagnetic materials.

Today's primary soft ferromagnetic materials in electric motors are iron and ferrosilicon alloys (2022). However, materials with lower eddy current and hysteresis losses have been developed since the 1970s.

After the energy crisis of the 1970s, the first attempts to use amorphous materials for electric motors were recorded (1981). Mischler et al., demonstrated the low-loss potential of the amorphous stator in a laboratory environment [82].

In 1967, a new class of materials, amorphous alloys, was introduced [83]. In the mid-1970s, interest in amorphous alloys based on iron and cobalt increased, and these materials began to find applications [84]. However, only in 1988 did Hitachi researchers investigate Nb and Cu additives. They added an annealing step to amorphous alloys to produce small-spaced crystallites of iron or cobalt within an amorphous matrix material. The formation of isolated crystallites of transition metals reduced the eddy current losses of these materials compared to traditional amorphous alloys. Despite a higher initial cost than silicon steel, these advanced alloys can reduce the total lifetime costs of electric motors due to reduced losses.

Currently (2022), unique treatments involving thermal manipulation, laser bombardment, and other technologies continue to produce high-performance magnetic materials.


**3.3 Healthcare value chain capabilities model**

Though the supply chains are widely used in manufacturing industry to start with, subsequently the supply chain concepts and practices have been applied in other sectors including healthcare industry, pharmaceutical, food and agriculture, ecommerce, humanitarian, disaster relief etc. Healthcare is changing at an unprecedented pace, due to the impacts of technology, cost pressures from both payers and patients who are seeking quality care. Healthcare organizations including providers, retailers, distributors and wholesalers, manufacturers. Some of the organization who have adopted supply chain practices include Johnson and Johnson, Cleveland Clinic, Mercy, CVS Health, McKesson, Novo Nordisk, Medtronic, Stryker, Roche, Pfizer, Owens and Minor etc. For example, Mayo Clinic has improved the care delivery and reduction in cost by collaborating with its suppliers and adopting digital technologies in its operations. **Figure 8** shows the framework suggested by Gartner in respect of healthcare organizations with a main objective of improving the human life at sustainable costs as well as quality. This model has five major processes viz., patient focus, collaboration, network visibility, cost to serve and change management supported by fundamental capabilities covering all the processes [11].

#### **Figure 8.**

*Healthcare value chain capabilities model [11].*

*Supply Chain Management and Restart of Economy in Post COVID-19 DOI: http://dx.doi.org/10.5772/intechopen.94207*

## **3.4 Sectoral specific supply chains**

Due to inherent advantages and capabilities of supply chains, many organizations across different industry/business verticals have adopted supply chains and benefited immensely. Some of the major sectors include automobile, food and agriculture, e-commerce, healthcare including hospitals, pharmaceuticals, diagnostic services, medical devices etc., defense and government, energy and power, oil and gas etc. Supply chains of e-commerce, food and healthcare is briefly explained in this section.

#### **3.5 Electronic commerce supply chains**

Electronic commerce (e-commerce) supply chains have gained significant importance due to ability of supply chains in meeting the customer service and low cost. Many companies like Amazon, flipkart, Alibaba etc. have demonstrated the power of supply chain in their business operations. **Figure 9** shows typical supply chain network of e-commerce supply chains. **Figure 10** shows a macro view of supply chain management at Amazon [Amazon.com]. e-commerce supply chains are more robust compared to others mainly due to its ability to manage the disruptions during crisis like COVID-19. Particularly during COVID-19 crisis, Amazon, flipkart and other e-commerce companies were able to maintain the continuity of supply in spite restrictions like lockdowns, social/physical distance and limited time operations, shortage of manpower etc. These companies are able to recover fast due to its resilience and responsiveness capability. This can be seen from the latest trend in the share price of e-commerce and food supply chain companies.

#### *3.5.1 Food supply chains*

A typical food supply chain with food safety information system and quality assurance system is shown in **Figure 11** [14]. The food supply chain includes farm/

**Figure 9.** *E-commerce supply chain [12].*

**Figure 10.** *Amazon supply chain [13].*

**Figure 11.** *Food supply chain [14].*

farmer, distributor, factory, distributor/retailer and final customer. In case of food supply chains the most critical issue is food safety across the supply chain. These supply chains focus very heavily into food safety and traceability at each stage of the supply chain mainly at interfaces. Food supply chains uses information and communication technology widely. Quality and Compliance of standards across food supply chain is very critical and makes use of advanced technologies like RFID, temperature controls, GPS enabled systems for tracking and traceability. It follows standards like good manufacturing practices, ISO standards and TQM etc. [14].

*Supply Chain Management and Restart of Economy in Post COVID-19 DOI: http://dx.doi.org/10.5772/intechopen.94207*

**Figure 12.** *Elements of healthcare supply chain [15].*

#### *3.5.2 Healthcare supply chains*

Healthcare supply chains are more complex than other supply chains due to presence of many stakeholders and responsiveness requirements. A typical healthcare supply chain is shown in **Figure 12**. Healthcare supply chains poses several challenges due to stringent regulatory requirements, safety and security and quality requirements. In spite all these challenges, many healthcare organizations benefited by adopting supply chain management approaches. According to Gartner study [11] on top 25 healthcare supply chains, top 5 organizations include Johnson and Johnson, Cleveland Clinic, Mercy, CVS health and Duke University Health system. Many of these organizations are using best practices like collaboration, digitalization, robust processes that are aligned with the overall objective as well as the elements listed in healthcare value chain capabilities model. The major strengths of healthcare supply chains include agility, alignment, adaptability, resilience and responsiveness. These organizations follow people, process and technology solutions in the care delivery. Of late, many healthcare organizations particularly using AI and Blockchain technologies for personalized care in large scale. Telemedicine and home care is growing very fast due to COVID-19 crisis where supply chain is very critical. Some of the organizations are using drones for delivery of medicines, pathology samples, food and equipment. Many start-ups also emerging in healthcare by bridging the gap predominantly through digital technologies and supply chains.

#### **3.6 Supply chain configurations (hub and spoke model, centralized vs decentralized SC)**

Supply chain network structures and its configuration is very important in achieving the performance of supply chains. Predominantly used supply chain structures in the practice include centralized and decentralized [2] or Hub and spoke model. **Figure 13** shows typical structure of centralized and decentralized supply chains. Centralized systems are more efficient and are generally used for

**Figure 13.**

*Centralized and decentralized supply chain system [2].*

**Figure 14.** *Hub and spoke model of a healthcare start-up [16].*

high volume low value commodities like steel, cement, automobiles, computers etc. where cost is important. Whereas decentralized systems are predominantly used in e-commerce, healthcare and other services where responsiveness is most important. Hub and spoke models are predominantly used is both product and service organizations. A typical hub and spoke model of a Start-up delivering health services in Rural areas in India is shown in **Figure 14**. Generally, the Hubs are equipped with more resources that can help serving the customers located spoke level. Typically, these share many resources and innovate through collaborative mechanism and employ multi skilled people and technology to improve the efficiency and reach.


*5.1. Inverter, Grid and Load Currents in Different Modes of Operation*

Figure 9 shows the current waveforms in Mode1 of operation. Since the PV array can produce more than the minimum power required for charging the battery and feeding the internal loads connected to the plant, the additional power produced by the PV array is supplied to the grid. An irradiance of 1000 W/m2 is adjusted on the user interface panel, hence the PV array is producing the maximum possible power. From the presented result, it can be observed that the grid current is phase displaced by 180 degree with respect to the inverter current.

**Figure 9.** Currents of inverter, grid, load, and voltage at PCC in Mode1 of operation.

In Mode2 of operation, an irradiance of 0 W/m2 is adjusted on the user interface panel; hence the PV array cannot produce any power. The battery is in charged condition and supplies the power to the load based on the Amp-hour rating of the battery and the discharging time or backup time adjusted by the user.

Since the local loads consume more than the inverter supplied current, the remaining current is drawn from the grid as shown in Figure 10. Since the load is drawing current from both the sources, the grid current and the inverter current are in phase with each other.

**Figure 10.** Currents of inverter, grid, load , andvoltage at PCC in Mode2 of operation.

In Mode3 Operation, the PV array cannot produce any power and the battery is in discharged condition. Since the battery is to be charged, the grid supplies the necessary charging current to the battery and the current required for the local loads as shown in Figure 11.

**Figure 11.** Currents of inverter, grid, load, and voltage at PCC in Mode3 of operation.

The dynamic response of the system to a step change in inverter reference power is shown in Figure 12.

**Figure 12.** Currents of inverter, grid, load for a step change in reference power.

When the inverter power reference is more than the local load requirement then the inverter is supplying current to grid and load. Since the grid is receiving the current, the phase displacement between grid and inverter currents is 180 degrees. After a step change in the reference power, since the reference power is less than the load requirement, the load current is supplied from both the inverter and the grid, hence the both the currents are in phase with each other. With the present controls, the system reaches the steady state within one cycle time.

#### *5.2. Battery Charger Input and Output Currents in Different Modes of Operation*

Battery current is considered as positive during charging and negative during discharging of the battery. The battery will be in charged condition in Mode1 and Mode3 of operations as explained earlier. During charging, depending on the SOC of the battery, the charging current reference is obtained and the controller carries the closed loop current control of the battery charger. The battery charger input and output currents for different modes of operation are discussed below. In Mode1 operation, since the battery is in charging condition, battery current and the average value of battery charger input current are positive, as shown in Figure 13.

In Mode2 of operation, when the PV array voltage is less than the minimum DC link voltage then the battery charger operates with closed loop voltage control and maintains a constant DC link voltage. The current through the battery depends on the Id Reference of the inverter which is obtained through the Amp-hour rating of the battery and the backup time required for the user. Since the battery is in discharging condition, battery current and the average value of the battery charger input current are negative, as shown in Figure 14.

**Figure 13.** Battery charger input and output currents in mode1 operation.

**Figure 14.** Battery charger input and output currents in mode-2 operation.

Similar to Mode1, in Mode3 operation battery current and the average value of the battery charger input current are also positive as shown in Figure 15. The charging current required for the battery is provided from the grid supply in this case.

**Figure 15.** Battery charger input and output currents in mode3 operation.

The dynamic response of the battery charger system is observed by applying a step change in the battery current reference. The system takes approximately 250 milliseconds to come to the steady state as shown in Figure 16.

**Figure 16.** Battery charger reference and actual currents for a step change in reference current.

### **6. Future Scope**

The results presented in this paper are obtained through real-time digital simulations. A scaled down model of the plant i.e., power circuit can also be made to test the controller and control algorithm. A predictive diagnostic in high-power transformers used in traction grade uninterruptible power supplies is presented in [20]. In similar lines, predictive diagnosis of the system components in a grid energy storage system can also be addressed as future work.

The presented system can also be extended for smart grid applications by incorporating additional energy sources along with the PV and battery, then as future work, the security and privacy problems in this smart grid can be addressed, as discussed in [21].

In this paper, design and control of grid energy storage system with a conventional PV inverter is explained in detail. Additional feature reactive power compensation can be incorporated to make the system work as PV-STATCOM. This system can also be extended for high power applications by using multilevel configurations for the PV inverter [22,23].


*7.2. Test 2: Sine Inputs*

The next test feeds a more complex signal composed of a sine wave with increasing frequency instead of a step signal, as shown in Figure 14. The test is conducted in order to validate the models for simple dynamic movements. As mentioned before, these cases are not explicitly captured by the FSS or training data. Figures 15 and 16 show the outputs.

The Set Membership followed the output of the system closer than in the previous test. It scored 93.0012% for pitch and 93.8389% for roll, much closer to the validation results. It is important to mention that the SM follows the dynamics and does not have the bias error observed in Test 1. Therefore, the FSS properly captures the continuous dynamic behavior, but it requires additional information to capture static behaviors, as required in Test 1. This is true also for the NN model, which also improved. It scored 98.1058% in pitch and 98.3087% in roll. The RLS roll output shows the disadvantages of this model. Due to the decoupling of the signal, while the initial movement causes little movement on the roll axis, RLS cannot process them and scores a worse fit than in the rest of the test. The fit scores are 78.4813% in pitch and 48.5090% in roll.

**Figure 14.** Test 2 input signal.

**Figure 15.** Test 2 results for pitch.

**Figure 16.** Test 2 results for roll.


**1. Introduction**

Ossification of the spinal ligaments impairs spinal mobility and occasionally leads to a spinal disorder [1,2]. Ossification of the posterior longitudinal ligament (OPLL) is common in Asian countries and can cause severe myelopathy [3]. Diffuse idiopathic skeletal hyperostosis (DISH), which is defined as ossification of the anterior longitudinal ligament bridging at least four vertebral segments of the thoracolumbar spine [4,5], has also been recognized as a pathological feature in patients predisposed to ossification and often coincides with the presence of OPLL [6–10]. Although DISH has been widely regarded as an asymptomatic disorder, it is unclear how it affects symptoms related to the whole spine. Few studies have compared patients with and without DISH in terms of clinical symptoms. Therefore, the Japanese Multicenter Research Organization for Ossification of the Spinal Ligament (JOSL), established a nationwide patient registry to prospectively collect the clinical and radiologic data, including whole-spine computed tomography (CT) scans, of OPLL patients. Using data from this registry, this paper focuses on differences in clinical and radiological findings between patients with and without DISH. We further sought to identify any significant associations between clinical symptoms and the severity of DISH in these patients based on patient-reported outcomes.

#### **2. Materials and Methods**

#### *2.1. Patients and Methods*

This multicenter prospective cross-sectional study used data from 16 member institutions of the JOSL established by the Japan Ministry of Health, Labour, and Welfare. The inclusion criteria were as follows: age ≥20 years; diagnosis of cervical OPLL based on radiographic findings; symptoms such as neck pain and upper and/or lower extremity numbness regardless of whether surgery was required, clumsiness, and gait disturbance; a visit made to a participating institution for symptoms between September 2015 and December 2017; and whole-spine CT scans available to determine the location of ossified lesions in the spine. The only exclusion criterion was a history of cervical spine surgery for OPLL. The study was approved by the institutional review board of each participating institution and conducted in accordance with the relevant guidelines and regulations.

#### *2.2. Clinical Evaluation*

Basic demographic and clinical data of patients were collected, including age, sex, diabetes mellitus (DM) status, body mass index (BMI), and presence of neck pain, back pain, and/or low back pain (LBP). Clinical status was evaluated using the following measures: cervical Japanese Orthopaedic Association (JOA) score [11], which is used for functional assessment of patients with cervical myelopathy, JOA Cervical Myelopathy Evaluation Questionnaire (JOA-CMEQ) [12], which assesses the function of the cervical spine, upper and lower extremities, and bladder as well as quality of life; and the JOA Back Pain Evaluation Questionnaire (JOA-BPEQ) [13], which assesses lumbar spine function, social dysfunction, mentality, locomotive function, and body pain. The degree of pain or stiffness in the neck or shoulders, pain or numbness in the arms or hands, and LBP was evaluated using a visual analog scale (VAS).

#### *2.3. Radiologic Evaluations*

CT images of the whole spine were collected for each patient. The images included the cervical, thoracic, and lumbosacral segments, spanning the occipital bone to the sacrum. The incidence of OPLL in the cervical spine from the clivus to C7 and in other spinal regions from T1 to S1 was evaluated on mid-sagittal CT images. Blinded to clinical outcomes, six senior spine surgeons (S.U., K.M., S.M., K.K., N.N., and K.T.) independently evaluated the images, as described previously [13]. OPLL was assessed as DISH if it completely bridged at least four contiguous adjacent vertebral bodies anywhere in the spine based on the criteria established by Resnick and Niwayama [5]. In accordance with a previous report [10], DISH was classified as follows: grade 1, DISH at T3–T10; grade 2, DISH at both T3–10 and C6–T2 and/or T11–L2; and grade 3, DISH extends beyond the C5 and/or L3 levels (Figure 1). To identify any significant differences in clinical findings, we compared patients with and without DISH and those with DISH according to grade. In addition, the ossification of the posterior longitudinal ligament index (OP-index), defined as the number of levels with OPLL in the whole spine [6], was also calculated for each patient.

**Figure 1.** DISH grading system. (**a**) No DISH; (**b**) Grade 1 (bony bridge at T3–T6); (**c**) Grade 2 (T2–T12); (**d**) Grade 3 (C2–L5). DISH, diffuse idiopathic skeletal hyperostosis.


**4. Conclusions**

This paper modeled the anomaly detection problem into a time series classification problem. The original time series undergoes data preprocessing and data augmentation to get a sample set with more uniform distribution, more obvious features, and smaller dimensions. Data augmentation includes data expansion and down-sampling. For small samples, the methods of symmetrical flipping, adding noise, and randomly generating outliers are used for data expansion, and samples with the same label are added without increasing the original samples. The down-sampling method of symmetrically extracting the maximum and minimum values can effectively reduce the dimensionality of the input sample and retain its features. Build a one-dimensional convolutional neural network model that is faster for time series classification problems. Adding the hyperparameter tuning of class weights makes the network more effective in dealing with an unbalanced training set. The method is verified with the acceleration data of a long-span cable-stayed bridge for one month. For the anomaly detection problem modeled as a time series classification problem, the results show that the proposed method can automatically detect a variety of data anomaly categories with high precision.

The proposed method can accurately identify most types of abnormal data, but for abnormal types with very inconspicuous features, such as outlier data, there is still much room for improvement in recognition accuracy. In future work, time series augmentation will not only be carried out in the time domain, but will be expanded to the frequency domain, or more advanced methods (such as GAN) will be used to expand samples.

**Author Contributions:** Conceptualization, Y.Z. and Y.L.; methodology, Y.Z.; validation, Y.Z. and Y.L.; investigation, Y.Z.; data curation, Y.Z.; writing—original draft preparation, Y.Z.; writing—review and editing, Y.L.; funding acquisition, Y.L. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research was funded by the National Key R&D Program of China via Grant No. 2018YFC0705606.

**Institutional Review Board Statement:** Not applicable.

**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** Restrictions apply to the availability of these data. Data was obtained from The 1st International Project Competition for Structural Health Monitoring with the permission of The 1st International Project Competition for Structural Health Monitoring organizing committee.

**Acknowledgments:** The raw data involved in this study were obtained from the organizing committee of the 1st International Project Competition for Structural Health Monitoring (IPC-SHM (2020)), and the authors thank IPC-SHM (2020) organizing committee for its valuable data resources.

**Conflicts of Interest:** The authors declare no conflict of interest.


**3. Conclusions**

20 New Technologies in the Oil and Gas Industry

(right) electroflocculation.

Note: Data: vol. = 3 L, t = 6 min.

life.

electrode. In the case of AC, the cyclical energization retards the normal mechanisms of attack on an electrode and makes this attack more uniform, thus ensures longer electrode

**Figure 8.** EF tests with high-salinity effluent. Legend: 60g / L NaCl: a) raw wastewater containing 60g / L of O&G; b) raw wastewater being mixed salt, for EF testing; c) effluent treated with AC (left) and DC

**a c b**

**Parâmeters Oily wastewater AC DC**  pH 6.4 6.7 6.7 Turbidity (NTU) 11050 8 10 Color (Abs.) 7.57 0.03 0.04 Salinity (g/L) 50.8 47.5 47.8 Conductivity (mS/cm) 91.5 87.4 87.0 TDS (g/L) 64.9 61.9 61.5 Phenols (mg/L) 0.5 0.2 0.2 Sulfide (H2S) (mg/L) 2.8 1.2 1.0 Ammonia nitrogen (mg/L) 36 4 5 O&G (mg/L) 60000 32 30 Mass electrode (g) - 0.18 0.26 Current (A) - 2.5 2.5 Tension (V) - 1.5 2.0

**Table 3.** Results of treating high-salinity effluent with AC and DC electrolysis.

In the present study, we could confirm that the EF process produces satisfactory results for treatment of oily wastewater, allowing its discharge into water bodies or reinjection in oil formations. The AC technology was highly effective, both with the original oily water as received and with the simulated produced water after addition of salt.

Overall, the results confirm the potential of the technique, which through simple and compact equipment, can be employed for the decontamination of organic compounds. The results of tests on oily water resulted in high organic load removal efficiencies, reaching 99% removal of oil and grease, color and turbidity, along with high removal of phenols, ammonia and sulfides.

The biggest advantage of AC versus DC electroflocculation is the lower electrode wear with the former technique. When using the same testing conditions and time of 6 minutes for both technologies, the efficiency was above 30%. The AC electroflocculation technique seems to be a promising alternative in the treatment of oily wastewater from the oil industry.


**2.2 Endocytosis**

*Gene Expression and Control*

Microbubbles can serve as vehicles for carrying genetic cargo and can be destructed by ultrasound, resulting in the local release of genetic payload. Meanwhile, sonoporation effect will occur upon which the bubbles are exposed to the appropriate ultrasonic energy, producing the transient small holes on the adjacent cell membrane and thus increasing the vascular and cellular permeability **Figure 1**. In this chapter, we will briefly introduce the mechanism and review the recent advances

*Schematic model of ultrasound-mediated gene delivery. Bioeffect produced by ultrasound and microbubble interaction could enhance the permeability of vascular and promote the accumulation of gene (green) in tissue.*

When ultrasound is irradiated locally with certain energy, the cavitation nuclei, such as ultrasound contrast agents and bubbles, could alternately occur expansion, contraction, splitting, fusion, and even rupture. This physical process is called cavitation effect. Accompanied by the cavitation effect, acoustic microstreaming, micro-jet, high temperature, and shockwave will occur in the medium, resulting in the formation of some temporary, reversible pores on the cell membrane, which is sonoporation [6, 7]. Generally, it is an accepted notion that the sonoporation from

There are a large number of studies, which have confirmed that sonoporation can increase the efficiency of gene delivery through enhancing the permeability of the cell membrane [9–12]. The number of pores, having a high impact on the gene delivery efficiency, can be affected by a lot of factors, such as acoustic pressure, irradiation duration time, and pulse repetition frequency [13–15]. Sonoporation pores trend to be larger along with the increase of acoustic pressure and irradiation time, which also enhance gene transfection efficiency [16]. However, excessive acoustic pressure or ultrasonic duration may reduce cell viability and even cause cell death, vascular rupture, and other side effects [17–19]. Therefore, to achieve a

about local gene delivery by ultrasound.

*(Quoted from: Sirsi and Borden [5]).*

**2.1 Sonoporation**

**Figure 1.**

**2. Mechanism of ultrasound-mediated gene transfection**

cavitation effect allows genes and drugs to enter cells [8].

**100**

In addition to sonoporation, cavitation effect can change the cell membrane structure through microstreaming and shear force. The mechanical force may cause cytoskeleton rearrangement and regulate various downstream cellular signaling pathways, helping the endocytosis of genetic cargo [20, 21]. Generally, there are three forms of endocytosis, including macropinocytosis, clathrin-mediated endocytosis, and caveolae-mediated endocytosis [22]. After ultrasound irradiation, the reactive oxygen species are produced to stimulate the calcium influx and induce the occurrence of endocytosis [23]. In addition, cavitation effect and shear force induced by ultrasound can change cell structure and influence endocytosis through mechanosensors and signaling cascade [24]. Meijering et al. demonstrated that endocytosis was involved in the uptake of the macromolecular substances, while small molecules enter cells mainly through the pores of the membrane surface [25].