Article
Development of Lift Control System Algorithm and P-M-E Analysis in the Workplace Inikuro Afa Michael Department of Computer Engineering, Taras Shevchenko National University of Kyiv, 01033 Kyiv, Ukraine;
[email protected]; Tel.: +380-63-226-1958
Received: 4 September 2018; Accepted: 10 October 2018; Published: 12 October 2018
Abstract: Lifts play an important role in human transportation in multi-storage buildings, which experience continuous improvements to their architecture and structure. As a result of these improvements, the development of efficient lift systems with more programs is required to meet these changes. In this work, a lift control system based on a programmable logic controller (PLC) is introduced, elucidating the development of the lift control algorithm and network based on a dispatching algorithm that utilizes a fuzzy system and exploits the traffic situation and condition. The PLC language ladder logic is implemented to facilitate a reduction in the average waiting time of passengers and the power consumption. Ladder diagrams for different scenarios are compared. The analysis of personnel-machine-environment (P-M-E) system conditions was conducted, examining numerous physical factors that could pose health and safety threats to workers. The present study opens doors for future lift systems studies based on PLC and the estimation of a safe workplace for machines and operators. Keywords: PLC; ladder logic; lift control system; P-M-E system; fuzzy systems
1. Introduction Lifts are essential motor-powered vertical media of transportation in residential, commercial and industrial buildings that play a huge role in the movement of people around these environments. Nowadays, as a result of tremendous development in the structural and architectural engineering in multi-storage buildings, lifts have become inevitable and a key requirement for human transportation [1]. Lifts are used in almost all the multi-storage buildings of metropolitan areas and hence, it is important to replace the traditional relay logic controlled lifts with more programmable technology based lifts for better efficiency, such as PLC [2,3]. These relay controlled systems have several limitations, such as a high fault ratio, difficulty in replacing flawed parts of the automated system and highly complex circuitry. Another drawback is the difficulty in providing fault tolerance using relay logic. PLC serves as a more enhanced replacement for designing modern lift control systems to circumvent these shortcomings and improve the troubleshooting of the system by allowing for easy monitoring of the inputs and outputs via human-machine interaction (HMI) devices, such as the HMI–LED indicator, better operational speed, reliability and relatively lower costs compared to other programmable control systems [4–8]. PLC has been successfully demonstrated in several control studies, including lift control systems [9–14]. When designing lifts with PLC, the dispatching algorithm is one of the most important aspects in the control system and therefore, an efficient algorithm can reduce the average waiting time of passengers to a remarkable average of 25 s or less and also reduce the power consumption of the lift system. Six main types of dispatching algorithms are generally implemented, which are namely: (i) Collective up—CU; (ii) Collective down—CD; (iii) Selective up—SU; (iv) Selective down—SD;
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(v) Selective-collective up—SCU; and (vi) Collective-selective down—CSD algorithms [5]. The choice of the preferred algorithm is selected on a specific instance based on the traffic amount and percentage. To achieve an efficient control system, the algorithm employs a fuzzy scheme to improve control based on logical reasoning and implementing systems through programmed expert knowledge. The concept of a fuzzy control system was first introduced by L.A. Zadeh as he introduced the concept of linguistic variables that serve as fuzzy sets (i.e., input variables in the fuzzy control) [15,16]. The fuzzy system is normally divided into four main parts, which are namely fuzzy knowledge rules, fuzzifier, fuzzy inference engine and the defuzzifier. This is done to transfer the input signal into linguistic terms and the inference makes the calculations and decision to prioritize certain lift assignment. Furthermore, the output information is converted by the defuzzifier into a single signal that serves as the control instructions [17]. The concept of fuzzy control and fuzzy logic has been extended to lift control and group control systems. The early to mid 1990s led to a boom in the implementation of fuzzy logic in lift systems [18–22]. Kim et al. [23,24] demonstrated a design based on a fuzzy control model that identifies traffic patterns and implements the traffic patterns and traffic mode based on information, such as traffic percentage, time, area-weight and other linguistic terms. Dewen et al. further demonstrated a fuzzy logic in group supervisory control, which demonstrates an optimum lift vehicle assignment with control devices [25]. Recent studies have introduced novel approaches for applying fuzzy logic in order to improve the expert prediction of lift control as compared to the old methods to increase efficiency in lift systems and energy optimization [26–28]. Jamaludin et al. further extended conventional fuzzy lift systems by introducing a self-tuning mechanism to adapt the control system to the continually changing traffic with better precision [29,30]. Some recent studies have demonstrated a lift system that employs fuzzy control systems and PLC. PLC is shown to be fast and adaptable to multiple inputs and outputs to meet traffic demands, which makes it suitable for this present study [31,32]. Other benefits of using PLC in this type of design is that it can be incorporated in more complex applications and can be easily adapted to other systems, such as the control of automated machinery systems, including cranes and robotic arm manipulator [33,34]. P-M-E refers to the optimal relationship between personnel (people in the work place and responsible for the operation of machine), machine (the computer and other control systems) and the environment (the prescribed work conditions for personnel–machine interaction). Even though fuzzy logic systems are very intelligent, they still lack the full mastery of the entire system, especially relating to installation, troubleshooting and maintenance. As a result, lifts can be considered to be a purely personnel-machine-environment system. Therefore, they require operators to oversee the optimal functioning. Sometimes, depending on the number of operators required, the conditions of the workplace change. Hence, the need for this analysis is to achieve a safe, highly efficient and cost effective system and work environment for the operators [35,36]. Lifts are considered to be vital assets in corporate buildings and as a result, its maintenance is paramount. In this paper, the development of the lift control network is briefly introduced in Section 2, with the development of the control algorithm explained; the fuzzy control system described based on its input variables, fuzzification, fuzzy inference and defuzzification processes; and the PLC tasks illustrated. The ladder logic diagram is introduced and compared for different scenarios in Section 2.2. Finally, the analysis of the P-M-E system in the workplace is discussed in Section 3. The present study presents a simplified lift control system using a PLC algorithm based on fuzzy logic scheme that can be easily implemented and adapted to other control system designs. 2. Control Network Development The lift system controller design operates with division zoning technique and a fuzzy control system for the efficient computing of fitting values Fp for a quicker lift hall-call. These fitting values computation is based on numerous lift performance conditions, such as the waiting time of the passengers, load capacity and distance between floor hall-calls. The controller implements a fuzzy
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system in traffic pattern recognition, while the division zoning scheme helps in tailoring the controller according to the patterns from the fuzzy system [23,24,37]. The fuzzy system used in this work is divided into three main parts: (i) fuzzification; (ii) fuzzy inference; and (iii) defuzzification. The fuzzifier helps to classify the traffic patterns by converting the signal into a set of fuzzy variables. The signal is translated into five linguistic terms, which are namely very large (VL), large (L), medium (M), small (S) and very small (VS). The traffic patterns are received in terms of the number of passengers going in different directions, which is namely upwards (UP) or downwards (DN), and also in the case of steady state traffic. The priority is given to the direction with higher traffic, i.e., if UP = VL and DN < VL (L, M, S, VS), Fp = High Priority is thus assigned to UP. Once the traffic direction is identified, the input information is passed to the fuzzy inference engine along with extra linguistic variables, such as (a) waiting time (WT); (b) space availability in lifts (SA); and (iii) distance between the elevators and distance of hall-calls floors and destination floors (Dist). The inference engine serves as the fuzzy decision block, which calculates the entire Fp to set the priority for the number of lifts (N) based on a rule sets (Fp = High, Medium or Low) as shown in Table 1. Table 1. Fuzzy knowledge rules for waiting time (WT), space availability (SA) and distance (Dist). IF
THEN (Fp )
WT = Short WT = Medium WT = Long
High Medium Low
SA = Large SA = Medium SA = Small
High Medium Low
Dist = Less Dist = Medium Dist = High
High Medium Low
This means that for a smaller loading, closer proximity of lifts, shorter waiting times and higher number of passengers waiting, the priority is assigned to a lift with highest combined Fp . These details are sent to the defuzzifier, which generates a single output based on the total priority assigned. This is conducted on the number of lifts (N) and the traffic mode is subsequently set. The defuzzification process employs the center of gravity method, which assigns the priority according to the total fitting values for 1 to N lifts. The lift with the highest total priority fitting value is assigned as the main preference and the information is passed as a single real traffic output. This output value serves as control instructions for responding to lifts according to the traffic data and hall-call assignment. In this section, we will look at the development of the lift control algorithm and the programming languages used. 2.1. Development of Lift Control Algorithm As stated previously, the algorithm employed is used to control the lift system through the division zoning and a fuzzy system. This takes into account the fact that the division zones represent lifts in the building, which are dependent on the hall-call requests. The present algorithm is comprised of three phases: (i) the identification in phase 1; (ii) the response in phase 2; and (iii) the execution in phase 3. In phase 1, the algorithm assigns zones with the aid of a fuzzy traffic controller, which was similarly described in the work of Patiño-Forero et al. [31], that identifies if a lift is free or not by analyzing information, such as the occupation and capacity of the lift on the floor from which the
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hall-call was made. Furthermore, it also utilizes the information related to whether this call was intended to 2goisupwards or downwards. Phase only initiated in a case of a free lift. In this case, the fuzzy system fitting value Phase 2for is quick only initiated in a case a free by lift.theInalgorithm. this case, Once the fuzzy fitting value calculations hall responses are of initiated the liftsystem is considered to be calculations for quick hall responses are initiated by the algorithm. Once the lift is considered to be occupied, phase 3 commences, in which the algorithm executes the inputted information from the occupied, phase 3 commences, in which the algorithm executes the inputted information from the hall-call until the lift is free again. The lift control algorithm employs an open platform hall-call until the (OPC) lift is free again. the The fuzzy lift control algorithm openwhich platform communication communication between control systememploys and theanPLC, is suitable for the (OPC) between the fuzzy control system and the PLC, which is suitable for the reception of data from reception of data from devices, such as HMI devices. The flowchart for the algorithm design is devices, as HMI shown insuch Figure 1. devices. The flowchart for the algorithm design is shown in Figure 1. The forfor controlling thethe movement of The main main task task of of the thedesign designisisrelated relatedtotothe thelogic logicthat thatisisessential essential controlling movement the lift between the floors of the building. The main conditions are stated as follows. (1) There must be of the lift between the floors of the building. The main conditions are stated as follows.(1) There upward button(s) to maketo a hall-call. If there is call, lift retains current must be and/or upwarddownward and/or downward button(s) make a hall-call. If no there is the no call, the liftits retains its position. In the cases of multiple calls from different floors, the response is made based on the time current position. In the cases of multiple calls from different floors, the response is made based on order of when thewhen call was made. The door of door the lifts willlifts have a programmed door that opens the time order of the call was(2) made. (2) The of the will have a programmed door that and closes automatically on every floor of the building. opens and closes automatically on every floor of the building. PLC programming languages languagesthat thatare aregenerally generallyused used control system design include PLC programming in in liftlift control system design include the the follows: (i) Structure (ST);Instruction (ii) Instruction list (IL); (iii) Function diagram (FBD); follows: (i) Structure text text (ST);(ii) list (IL); (iii) Function blockblock diagram (FBD); (iv) (iv) Sequence function and (v) Ladder (logic) diagrams Ladder is a Sequence function chart chart (SFC);(SFC); and (v) Ladder (logic) diagrams (LL/LD).(LL/LD). Ladder logic is a logic graphical graphical programming language that is extracted from the circuitry evolution of the relay control programming language that is extracted from the circuitry evolution of the relay control wiring [13]. wiring [13]. In work, this present work,logic, the ladder is the mostused commonly used languagethe to In this present the ladder which logic, is the which most commonly language to program program the PLC, was employed. PLC, was employed.
Figure 1. 1.Flowchart Figure Flowchart representing representing the the algorithm algorithm execution execution in in different different phases.
2.2. LadderLogic Logic 2.2.Ladder The ladder logic logicnetwork networkisisestablished establishedbased based pre-selected PLC prerequisites, such as The ladder onon thethe pre-selected PLC prerequisites, such as the the input signal from the hall-call. Some of the ladders that are responsible for tracking the status input signal from the hall-call. Some of the ladders that are responsible for tracking the status of of different pushes are described in Figures 2 and 3. different pushes are described in Figures 2 and 3. Ladder rungs, which which are are Ladder diagrams diagrams are are interpreted interpreted from from left left to to right right and and from from top top to to bottom. bottom. The The rungs, also referred to as networks, have several control elements with a single output coil. Table 2 describes also referred to as networks, have several control elements with a single output coil. Table 2 the logic input information from the ground floor as illustrated in networkin1 network of Figure12a. describes the logic input information from the ground floor as illustrated of Figure 2a. Table 2.Logic input information from the ground floor as seen in Figure 2.
Symbol indcatr_Gnd
Address Q0.0
Comment indicator of ground floor request
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Table 2. Logic input information from the ground floor as seen in Figure 2. Appl. Syst. Innov.2018, PEER REVIEW Symbol 2, x FORAddress Appl. Syst. Innov.2018, 2, x FOR PEER REVIEW
indcatr_Gnd
Max MaxEntries_Qu Entries_Qu Max Entries_Qu Req_Gnd_Floor Req_Gnd_Floor Req_Gnd_Floor
Q0.0 VWO VWO VWO 10.0 10.0
10.0
Comment
5 of 10 5 of 10
indicator of ground floor request maximum no. of entries in the queue/starting address of table maximum no. of in the queue/starting address of table maximum no. entries of entries in the queue/starting address of table request coming from ground request coming from ground floorfloor
request coming from ground floor
Figure 2.Ladder diagrams for: (a) Reception and storage of information from touch sensor on the Figure diagrams for: for: (a) Reception Reception and touch sensor onon thethe Figure 2. 2.Ladder Ladder diagrams andstorage storageofofinformation informationfrom from touch sensor ground and first floor represented as networks 1 and 2; and (b) Storage of information related to the ground and first floorrepresented representedas asnetworks networks 1 and 2; and (b) Storage ofofinformation related to to thethe ground and first floor 2; and (b) Storage information related current position of the lift. current position thelift. lift. current position ofofthe
It is important to take a look at the ladders tracking the touch sensors. We can see that from importanttototake takeaalook lookatatthe the ladders ladders tracking tracking the seesee that from It It is is important the touch touchsensors. sensors.We Wecan can that from Figure 2, the normal open contact here is responsible for receiving and storing the information Figure 2, the normal open contact here is responsible for receiving and storing the information Figure 2, thefrom normal is responsible for receiving and storing the information received the open touchcontact sensor.here After this, the second symbol stores the position of the lift.received The received fromsensor. the touch sensor. After this, symbol the second symbol stores the position of the lift. The is from the touch After this, the second stores the position of the lift. The information is sent to the counter for processing and the position of the lift is stored in information the counter information is sent the counter forthe processing and is stored in the sent to the forto processing and position of thethe liftposition is storedofinthe thelift counter ready for counter execution. ready forcounter execution. ready for execution.
Figure 3.Ladderdiagrams diagrams Combining, storing checking all required conditions; (b) Figure 3. Ladder for:for: (a)(a) Combining, storing andand checking all required conditions; (b) Driving Figure 3.Ladder diagrams for: (a) Combining, storing and checking all required conditions; (b) the conditions in theand output; and (c) Automated movement of theof doors of the lift. theDriving conditions in the output; (c) Automated movement of the doors the lift. Driving the conditions in the output; and (c) Automated movement of the doors of the lift.
The ladder diagram in Figure 3a is responsible for combining and storing all the conditions The ladder diagram in Figure 3a is responsible for combining and storing all the conditions received (i.e., ladders for checking all required conditions). Based on the results of this condition, the received (i.e., ladders for checking all required conditions). Based on the results of this condition, the
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The ladder diagram in Figure 3a is responsible for combining and storing all the conditions received (i.e.,motor ladders for checking conditions). Based themotor resultsexecutes of this condition, output (i.e., drive) is driven all by required the ladder seen in Figure 3b.onThe its action the output (i.e., motor drive) is the driven byladders. the ladder in Figure 3b. conditions The motor include: executesnext its action from the output received from other Theseen examples of the floor from the output received from the other ladders. The examples of the conditions include: next floor waiting for service, the current lift position and next destination, etc. waiting for service, the current lift position and next destination, etc. The door of the lift is also automated based on the movement of the lift, which means that when The of the the lift is alsoof automated based on theand movement of theopen lift, which the lift is door in motion, door the lift will be closed will remain for themeans rest ofthat the when time. the lift is in motion, the door of the lift will be closed and will remain open for the rest of the time. The ladder to achieve this goal is shown in Figure 3c. The ladder to achieve this goal is shown in Figure 3c. 3. P-M-E System Analysis in the Workplace 3. P-M-E System Analysis in the Workplace Labor protection is important for creating a workplace with safe and healthy labor terms. The important for creating a workplace with safe and healthy labor terms. majorLabor labor protection protection is terms are examined in order to reduce the influence of any dangerous work The major labor protection terms are examined in order to reduce the influence of any dangerous work environment factors on workers[38,39]. Therefore, P-M-E system analysis is done as described in environment factors on workers [38,39]. Therefore, P-M-E system analysis is done as described in Figure 4, showing the relationship of personnel (P), machine (M) and environment (E). Figure 4,The showing the relationship of personnel (P), machine (M) and environment (E). important part of this project was conducted in the workplace of a small lab with The important part of this project was conducted the room workplace of a small lab dimensions 2. with dimensions of 8m×6m×4m. Accordingly, the area ofinthe is equal to 48m The area of the 2 . The area of the windows was of 8 m × 6 m × 4 m. Accordingly, the area of the room is equal to 48 m 2 windows was 3m×2m = 6m . The workplace has double-sided windows and a door, which allows for 3 m amount × 2 m = 6ofm2air . The workplace double-sided windows door, which allows amount an entrance forhas ventilation. The width and of athe evacuation exitfor is anequal to 2 . In the of air entrance for ventilation. The width of the evacuation exit is equal to 2 m × 0.8 m = 1.6 m 2 2m×0.8m=1.6m . In the workplace, there are five people (p=5) working on different projects and they workplace, there are five people (p = 5)functions workingfor onthese different projects and they all all use computers to operate particular projects. An equipment inuse the computers workplace to operate particular functions for these projects. An equipment in the workplace feeds from the feeds from the three-phase, four-wire electric system with the dead earthed neutral, as shown in three-phase, four-wire electric system with the dead earthed neutral, as shown in Figure 5. This has a Figure 5. This has a tension of 380/220V and a working tension of 220V. Furthermore, the working tension of 380/220 V and a working tension of 220 V. Furthermore, the working frequency was 50 Hz. frequency was 50 Hz. With regards to the terms of labor, the volume of workplace should not benot lessbe than m3 With regards to normal the normal terms of labor, the volume of workplace should less20than 2 andmarea of 6area m forone of the PC.ofIn the this PC. present study, we ranstudy, the following the 3 and 2forone operator 20 of 6moperator In this present we rancalculations: the following 2 3 area (A) of working 8m×6m = 48= m and the volume (V)volume = 8 m ×(V) 6m × 4 m = 192=192m m . At 2 and the 3. calculations: the areaplace (A) of=working place 8m×6m =48m =8m×6m×4m 2 and volume/People = 192/5 = 41 m3 . Hence, the present, the area/no. of people = 192/5 = 10.6 m 2 3 At present, the area/no. of people = 192/5= 10.6m and volume/People = 192/5= 41m . Hence, the volume and and area area on on one one operator operator of of the the working working place place are [40,41]. volume are in in accordance accordance to to the the terms terms of of labor labor[40,41].
Figure 4.The Figure 4. Thegeneral generalstructure structureof ofthe theP-M-E P-M-E system system with with descriptions descriptions in in Table Table 3. 3. Table 3. List of connections in the general system of P-M-E shown in Figure 4. Number of Connection 1
Directions P1-M1
Comment Influence of personnel on management
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Table 3. List of connections in the general system of P-M-E shown in Figure 4. Appl. Syst. Innov.2018, 2, x FOR PEER REVIEW
Number of Connection 2 1 3 2 4 3 5 4 5 6 6 7 7 8 8 9 9 10 10 11 11 12 12 13 13 A A
Directions M1-P1 P1-M1 M1-TW M1-P1 TW-P3 M1-TW P3-P1 TW-P3 M2-P3 P3-P1 M3…M7-E M2-P3 M3 E-P3…P7 . . . M7-E E-P3 E-M1 . . . P7 E-M1 P1-M2 P1-M2 P2-E P2-E P3-P2 P3-P2 M1-M2 M1-M2 M2-M1 M2-M1 system TheThe system of external control of external A- P1 A- P1 control
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Comment State information machine processed by personnel Influence on the management Influenceofofpersonnel machine on goal of work State information machine processed by personnel Influence of the goal of work on the psycho-physiological state of personnel Influence of machine on the goal of work Influence of the state of organism of personnel on quality of his work Influence of the goal of work on the psycho-physiological state of personnel Personnelofunder theof influence ofof dangerous factors Influence the state organism personnelproduction on quality of his work Influence of machine on an environment Personnel under the influence of dangerous production factors Influenceofofmachine environment the state of organism of personnel Influence on anon environment Influence of environment on the of organism of personnel Influence of environment on thestate machine Influence of environment on the machine Influence of personnel on the emergency state of machine Influence emergency stateon of an machine Influenceofofpersonnel personnelon asthe a biological object environment Influence of personnel as a biological object on an environment Influence of the psycho-physiological state on the intensity of exchange of Influence of the psycho-physiological state on the intensity of exchange of matters between an organism, environment and physiology of personnel matters between an organism, environment and physiology of personnel Necessaryinformation informationfor formaking makingemergency emergency influence Necessary influence Managingemergency emergencyinfluences influences Managing Managing about technological process from the external Managinginformation information about technological process from the external control controlof ofthe thesystem system
1.Calculation of current passing through the body of man a unipolar bipolar touch TaskTask 1. Calculation of current passing through the body of man at a at unipolar and and bipolar touch.
Figure 5.The body a man a unipolar bipolar touch. Figure 5. The body of a of man at a at unipolar and and bipolar touch.
In this variant, a man touches phase wires (biphasic touch). In this a current flowing In this variant, a man touches twotwo phase wires (biphasic touch). In this case,case, a current flowing through the human body be calculated using formula: through the human body can can be calculated using this this formula: Vlinear IpeopleV= linear R people Ipeople = Rpeople whereVlinear is the linear voltage =380 V;Rpeople is the resistance of people = 1.4; and Ipeople: current of people = unknown. Tovoltage calculate theV; value of current, we use the following formula: where Vlinear is the linear = 380 Rpeople is the resistance of people = 1.4; and Ipeople : current
of people = unknown. To calculate the value of current, 380we use the following formula: Ipeople = = 0.27 A 1.4 × 103 380 = 0.27 A I = This current (271mA) with people 50-Hz frequency 1.4 × 103 causes cardiac arrest without fibrillation. If the effect of the current last 1 to 2 s and causes no damage to the heart, a person usually resumes normal This current (271 mA) with 50-Hz frequency causes cardiac arrest without fibrillation. If the effect activity on their own after the power failure. of the current last 1 to 2 s and causes no damage to the heart, a person usually resumes normal activity on their after the power failure. Taskown 2.Calculation of crossing of send-offs and cables for the economy of density current Task 2. Calculation of crossing of send-offs and cables for the economy of density current. The formula for its calculation is given as: The formula for its calculation is given as: Imax Sec = J Imax ec Sec = where Imax is the current line during the normalJec work of network with a SI unit of A; and Jec is the economical current density with a SI unit of A/mm2, which is determined depending on the material and time of usage of the maximal loading. In the case of bare copper conductors with current, Sec = 9 = 3 mm2 . Anything less than 3mm2 can cause electrocution due to the high current flowing 3.0
through the copper wire, which increases the heat and causes the wire to change to heated red color.
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where Imax is the current line during the normal work of network with a SI unit of A; and Jec is the economical current density with a SI unit of A/mm2 , which is determined depending on the material and time of usage of the maximal loading. In the case of bare copper conductors with current, 9 Sec = 3.0 = 3 mm2 . Anything less than 3 mm2 can cause electrocution due to the high current flowing through the copper wire, which increases the heat and causes the wire to change to heated red color. Task 3. Estimation of shut-down ability of devices maximal current defense. The short circuit current, Ish is calculated as Ish =
Vph Zph−0 ,
where Vph is the phase tension with a SI
unit of V; and Zph-0 is an impedance of loop a «phase-zero» with a SI unit of Ω. The device of maximal current defense is provided by the reliable disconnection of users of electric power from the network if a condition is executed, which is calculated as: Inom ≤
Ish Eˆ
where Inom is the nominal current of the fusible insertion of safety device. The current electromagnetic insertion of circuit breaker on short-circuit has a SI unit of A. Furthermore, Eˆ is a coefficient of multiples of current (according to NPAOP 40.1-1.21-98 [42] for fuse Eˆ = 3 or for the electromagnetic breaker, Eˆ = 1.4 or 1.25). For a fuse: Vph 220 V Vph = 220 v; Zph − 0 = 20 Ω; Ish = = = 11 Zph−0 20 Ω Ish 11 = = 3.66 ˆE 3 Inom ≤ 3.66
Inom ≤
Another important task is the calculation of the necessary amount and types of fire-extinguishers. For safety purposes, the computer room should be provided with these types of denotation of fire extinguisher: (i) BBk-1,4, BBk-2 Carbon-dioxide and (ii) BBk-3,5, BBk-5 Carbon-dioxide. Fire safety is an important condition of security of the personnel, property, society and state from fires. In addition to the provision of fire extinguishers, alarm systems are installed for the detection of fire by initiating audiovisual signals as hazard warnings. 4. Conclusions In this paper, the development of the lift control system algorithm is discussed. It is shown that the network development is based on the traffic patterns and the zoning division using the fuzzy lift control system. The ladder logics for understanding the evolution of the electrical circuitry of the PLC controlled lift system are discussed and compared. The personnel-machine-environment system analysis is conducted to ensure not only the safety of workers but also the smooth operation of the machine and the workplace. The present study provides an insight for future studies that should focus on the implementation of lift control systems and creating an excellent working environment for their efficient operation. Funding: This research received no external funding. Acknowledgments: The author acknowledges the support of the research technicians of the Faculty of Computer Engineering of the Kharkov National University of Radio-electronics and the regular research visits hosted. Conflicts of Interest: The author declares no conflict of interest.
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