Due to increased urbanization, online ordering and e-commerce, logistics companies face numerous challenges in meeting customer demands in the city. The application of new strategies and business models, trends of increasing frequency and decreasing the delivery size additionally affect the complexity of the challenges in CL. In the processes of preparing goods for delivery in logistics centers, MH processes play one of the key roles. Optimizing the MH process can contribute to overcoming various challenges in CL.
Accordingly, this paper aims to rank and select smart solutions for MH activities for a logistics center of a leading German logistics company in the Serbian market. Solutions are based on combinations of modern MH equipment and I 4.0 technologies. The main activity of the logistics company is the preparation and delivery of consumers’ goods for the City of Belgrade. The investigated company uses a fleet of electric forklifts for MH activities and the preparation of goods for delivery. It was estimated that, by engaging smart MH solutions, the company can respond more efficiently to customers’ requirements and improve its competitive position in a vulnerable market. Customers’ requirements in the city are characterized by frequent deliveries, small quantities, pre-defined time windows and a variable assortment of goods. Limitations, such as traffic jams, delays, insufficient utilization of transport capacities and negative environmental impacts, create additional motivation for engaging smart MH technologies in the company’s logistics center. Although there are numerous challenges in the logistics processes of the company, some of the key ones concerning MH activities in logistics centers are as follows:
Due to the existence of time windows in which it is possible to deliver goods to the city, any delay in the execution of logistics activities in a company has a negative impact on customer service. Incorrectly and inefficiently made deliveries lead to direct customer dissatisfaction. Solutions based on modern MH equipment and I 4.0 technologies provide high efficiency, low operating costs, high work safety, less possibility of error and damage to goods, etc., which create conditions for sustainable business for the company.
4.1. Defining Alternative Smart Solutions
This paper proposes (smart) solutions based on modern MH equipment, such as SAGV forklifts, AMRs, GTP and UAVs, as well as I 4.0 technologies, such as the Industrial Internet of Things (IIoT), Global Positioning System supported by CC-Cloud GPS (CGPS), RFID, BD, DM, AI and AR with integrated Decision Support Systems (DSS) and Warehouse Management Systems supported by CC-Cloud WMS (CWMS). With IIoT sensors [
79,
80] and RFID tags [
81,
82], communication is carried out between every device and element in the warehouse. IIoT sensors record and update information on warehouse operations. The routing and navigational functions of smart MH equipment depend on CGPS [
83,
84]. The system that integrates and monitors all warehouse operations is known as CWMS [
85,
86]. Data regarding every process in the warehouse is gathered, examined, and processed using BD and DM technologies [
87,
88]. With the combination of AI and AR, the DSS is a system that offers several bases that make it simpler for managers to make decisions [
89].
SAGV forklift (A1). AGVs have widespread use in MH operations within the automation of storage technologies. One of the categories of AGVs is the AGV forklift, which is considered the most commonly used equipment for transport and MH operations in modern smart systems [
90]. Unlike the traditional driverless AGV forklift, which is controlled by a central computer and generally has a fixed route, the Smart AGV (SAGV) forklift includes its own computer, providing logistics operations with more flexibility and independence from other forklifts in the fleet [
90,
91,
92]. The mobility of smart AGVs is possible with the support of CGPS and RFID technology. CGPS technology enables the management of MH equipment in warehouses (this technology provides data on the position of MH equipment in real-time) [
93,
94]. Moreover, RFID tags are used to indicate the appropriate location where the next warehouse assignment should be accepted. The SAGV forklift communicates with the control system via a Wi-Fi network that connects all RFID and IIoT sensors [
79,
80,
81]. SAGV forklifts have safety scanners that operate based on AR, which prevent them from encountering barriers such as employees, equipment, goods, etc., thus providing high-level work safety [
88,
91,
92,
93,
94,
95]. CWMS is necessary for the communication of all connected entities (MH and other equipment, goods, etc.) with the central computer. The primary functions that a CWMS should provide are information on inventory status, the planning and scheduling of an assignment to MH equipment, the arrival time and position of external transport vehicles, the execution of an assignment and order status [
84]. In the system, all MH equipment and other equipment has an IIoT sensor that collects and saves data about their current state and potential damage due to collisions. In autonomous technology, it is required to protect and process a considerable amount of data, which can be performed with the support of BD and DM [
86,
87]. BD helps collect and save data on routes, performed warehouse assignments, serviced warehouse locations, the time required to perform each warehouse assignment, information on the times of orders’ fulfillment, the level of errors during order picking, the degree of damage to an assignment and order status. The collection and processing of these data are provided using DM. The processed data from AI technology in integration with DSS is used as input data for determining the optimal route, the order of performing warehouse assignments, storage and retrieval strategies, etc. Considering the foregoing, SAGV forklifts have the imperative to become one of the main automation technologies in logistics centers oriented toward improving customer service in the city [
90,
91,
94].
The advantages of SAGV forklifts are their high positioning accuracy, significant lifting height and functionality in narrow corridors, resulting in increased utilization of storage area by 30–40% compared to traditional electric forklifts and in the increased efficiency of customer service [
91,
92,
93,
94]. The social sustainability of SAGVs is mainly related to the humanization of MH. Reducing labor costs, improving inventory management and reducing employee errors are just some of the key elements of the economic advantages of this alternative. Environmental sustainability is primarily manifested through the use of electricity for propulsion, which significantly contributes to reductions in greenhouse gas (GHG) emissions, including a low noise level in work environments. Some of the key disadvantages are relatively high investment costs, increased maintenance costs, additional employee training requirements, etc. [
92,
93,
94].
AMR (A2). AMRs symbolize a fully automated system that can independently complete intralogistics activities because it uses onboard sensors and processors for automatic MH without the need for physical controls [
96]. Routing in the AMR system is accomplished using CGPS, which traces the asset’s location in real time and provides coordinates for further movement [
97]. In contrast to traditional AGV systems with a fixed route, AMRs have much greater flexibility because of AI and AR support [
89]. With the support of AI and AR, AMRs “learn” their environment by registering its own location and then dynamically plans routes based on current environmental conditions and logistics requirements [
88,
89]. When barriers arise on a defined route, AI technology as a base component of AMRs at the same time reorganizes and re-optimizes the route to the next point [
98,
99]. BD collects data on completed assignments and routes as a base for DM to optimize the route to the next warehouse assignment [
86,
87]. Because AMRs do not have the possibility of active pick-up and disposal of material, IIoT technology provides adequate information about the engagement of pick-up mechanisms, such as robotic arms, as well as collaboration with other equipment, such as cranes [
78,
79,
97,
98,
99,
100]. Thus, upon completion of the warehouse task, the CWMS data provided by the BD is forwarded to the auxiliary equipment, which, at that moment, engages in the next MH position [
84]. As with SAGVs, the basic task of CWMS is to provide all the necessary information that is a prerequisite for performing the warehouse assignment, which is related to the position of the external transportation vehicle, its start and end times in MH activities, the contents of deliveries, and the process of performing intralogistics activities [
97]. AMRs are a contemporary technology that provides additional benefits in implementation due to its simple integration into the existing storage system and effective engagement when other technologies fail in MH activities [
98,
100].
The main advantages of AMRs are high flexibility in material transport, the possibility of autonomous decision making, reductions in crossing flows, etc. [
99,
100,
101]. Lowering the cost of logistics activities, such as maintaining low operating and maintenance costs, contributes to economic sustainability. Reductions in employees engaged in MH activities significantly increases work safety, which also makes this alternative socially sustainable. Environmental sustainability is reflected in the use of electric energy for propulsion, which completely eliminates GHG emissions and produces low noise levels. However, AMRs have challenges in terms of management, IT support and updating data. One of the main disadvantages is not having the ability to actively load freight. As a result, robotic arms, cranes or other devices that can provide pick-up of the load need to be used on transshipment decks [
55,
56]. Lower capacity and speeds, including longer battery charging times for AMRs compared to AGV forklifts, are some of the additional limitations that require consideration when employing them for MH activities [
97,
98,
99].
GTP (A3). GTP represents an automated system that integrates an AMR and an Automated Storage and Retrieval System (AS/RS) to increase the efficiency of MH activities in logistics centers. In some ways, this technology is an upgrade to AS/RS, which, in addition to automatic storage and retrieval, also performs order-picking activities [
102,
103]. By applying CWMS, goods are stored in predefined locations, from which they are picked up and automatically transported directly to the picker, eliminating unnecessary movement time and providing accurate stock data [
84,
102]. Consequently, using AMRs increases the efficiency of employees, and AS/RS has high warehouse density and commodity flow. In this contemporary warehouse system, racks and/or shelves are used to hold inventory and are also in a high-density arrangement on the floor. According to MH requirements, the AMR moves under the rack and raises it to a position at the appropriate place. With the help of IIoT shelf sensors and AMRs, safe movement within the logistics center is ensured [
79,
80]. BD technology saves and stores data from CWMS and sends it in the appropriate format to DM technology for processing. The data refer to the sequence of order execution, the number of requested goods, the direction of delivery as well as other relevant information that is necessary for the efficient execution of the order [
85,
86,
87]. These data can also be used when defining the order of rack positioning. The pick-up–delivery station, as one of the most responsible entities in MH, can have a classic configuration with only a monitor and scanner, but it can also be supported by Pick by Vision technology and scales, and can be equipped with packaging material and other equipment for finalizing warehouse assignment. The mentioned and other demanding tasks can be effectively performed by engaging AI and AR technologies, thus providing employees with timely information about the goods they handle [
99,
102,
103,
104]. In this way, repetitive and frequent activities are minimized to the point of elimination, and the abilities and skills of the employees are directed toward the improvement of the MH process, thus contributing to more efficient customer service [
103,
104].
The GTP system is designed to reduce the workload of employees, provide high storage density and improve inventory flow. The system’s ability to handle a wide range of goods makes it suitable for the reallocation of orders, easy replenishment of inventories, and other logistical activities. The GTP system automatically locates and stores goods to increase throughput and utilization, increases precision and enables delivery on the same day as the order is received, which is especially significant in the city [
102,
104]. Using GTP increases accuracy and, at the same time, eliminates errors during ordering, which is extremely important in systems in which there is a high daily demand (e-commerce). Reducing the costs of logistics activities in the GTP system contributes to economic sustainability. The elimination of human labor significantly increases work safety, which makes this alternative socially sustainable. Environmental sustainability is reflected in the use of electric energy for propulsion (thus eliminating GHG emissions) and low noise levels [
104,
105]. Using a CC-hosted WMS, GTP can be efficiently controlled to automate the picking process, bringing goods directly to the operator. The main disadvantages of this technology are high implementation costs, less flexibility due to a fixed number of storage locations, a lack of flexibility concerning changing requirements, and, in the event of a failure, long downtimes of the system [
103,
105].
UAV (A4). UAVs are defined as cargo aircrafts that operate autonomously without pilots. The main benefits of their implementation are reflected in 3D navigation for MH activities [
106,
107,
108]. Although UAVs are effectively used for control and logistics activities throughout the SC, they are particularly suitable to increase the effectiveness of logistics processes, especially the transportation of goods within the warehouse. UAVs usually function flawlessly in narrow and high warehouse corridors [
106,
109]. The use of UAVs is notably effective for the implementation of intralogistics activities within production systems. This alternative contributes to saving time and space in the warehouse, which contributes to its application in inventory management [
108,
109,
110,
111]. With the application of AI technology, UAVs can be operated automatically and without the need for direct human supervision. Navigation and management are performed using CGPS systems and IIoT sensors that provide the necessary data on the positions of equipment and drones [
79,
83]. CWMS is necessary for the communication of all MH and other equipment and goods with the central computer. CWMS should provide information on inventory status, the planning and scheduling of an assignment to a UAV, assignment location, arrival time and the positions of external transport vehicles, the execution of an assignment and order status [
85]. The necessary data on the locations of goods, employees and equipment are obtained using IIoT sensors and are stored using BD technology [
80,
86,
88]. In addition, IIoT collects data on the readiness of goods for unloading and storage and on the time and place of positioning the external transport vehicles and UAVs, thus preventing crashes of UAVs and collisions with other equipment [
79,
84]. The collected data are processed and analyzed with DM technology, and thus, the sequence of serving the storage locations and the service time are determined. Moreover, DM has an essential role in UAV routing, thus achieving high security at the warehouse location where goods are picked and delivered [
86,
88,
107,
111]. However, for this alternative to be effective, clearly defined laws and regulations are needed, as well as a developed awareness of acceptability among employees [
87].
The possibility of continuously and precisely performing intralogistics activities, reduced operating costs, minimized maintenance costs and increased safety in logistics centers, are the main advantages of UAVs [
109,
110,
111,
112]. This alternative is environmentally and socially sustainable because it is electrically powered and does not require drivers [
107,
108,
111]. Some limitations relate to technical characteristics, such as a low payload, limited range and frequent battery charging requirements. In addition, significant initial investments call into question economic sustainability. Therefore, they are often used in combination with other autonomous alternatives [
107,
108,
109,
110,
112].
4.2. Evaluation Criteria for Smart MH Solutions
The optimal alternative solution is selected using the MCDM method, which necessitates the formulation and selection of relevant criteria for evaluating proposed alternatives. To select the optimal MH equipment, criteria are grouped into three groups: technical–technological, economic and normative. The criteria are defined based on numerous previous studies in the field of MH equipment selection. Below is a description of the defined criteria.
Technical–technological criteria:
Efficiency (C1) represents the total time that is required for the implementation of logistics activities per order, from the moment of receiving the order to the moment of delivery the goods. The alternative that requires less time to complete the task is preferred. [
113,
114,
115].
Technological development (C2) suggests the degree of technological development, which implies the level of its application in practice. The alternative that is more often used in practical applications is favored [
116].
Utilization complexity (C3) includes the time taken to implement the technology and the ability to integrate the technology with other or existing systems. It assumes the ability to connect with existing information systems, such as CWMS, IIoT, sensors, etc. A technology that requires less time for implementation is favored over others [
113].
Impact on MH system resilience (C4) represents the velocity of technology’s response to unpredictable circumstances (cancellation, increase in volume requirements and the growth of the warehouse system). Accordingly, technology that has the quickest response time is more favorable [
112].
Smart handling (C5) represents the consolidation of MH activities to reduce or eliminate the engagement of employees. Contrary to traditional MH technologies, which imply the participation of employees in practically all MH activities, progressive technologies based on I 4.0 partly or completely eliminate such requirements. Therefore, technology that can independently perform several operations is more favorable [
117].
Energy consumption (C6) is the total amount of energy that is required for MH equipment to finish a task. Therefore, technologies with lower energy consumption are more favorable [
112,
117].
Economic criteria:
Procurement costs (C7) represent the initial investments for the implementation of the alternative, including the expenditures for adapting the technology to the existing ones. According to this criterion, technology that requires less investment is more favorable [
112,
114].
Labor cost savings (C8) represent lowering the costs for employee wages. An alternative that can perform multiple operations independently requires fewer employees, thus reducing costs. In addition, it also includes the difference in the total costs of operating the new technology system in relation to the operation of the existing system [
113].
Maintenance costs (C9) include the costs of servicing, infrastructure maintenance, etc. Lower costs indicate that technology is more favorable regarding this criterion [
112,
118].
Return on investment (C10) indicates the time that is required for a return on an investment. A shorter period suggests that the alternative is more favorable regarding this criterion [
113,
119].
Normative criteria (standardization and regulation):
Employee safety (C11) indicates the adopted standards on occupational safety and health (IMS, ISO 45001), and the degree of their respect. Standard adoption can reduce the number of injuries and their severity. Technology that has a higher degree of automation is safer [
118].
Warehouse safety impact (C12) refers to employee injuries and damage to goods, storage equipment and other tools, devices and MH elements. Sophisticated I 4.0 technologies are mostly automated, so an alternative that communicates more with the environment and is resistant to human error is more favorable [
118].
Standardization (C13) indicates the adaption of existing local norms to global regulations to improve the operational environment. The alternative that has the most elevated degree of compliance with global standards is more favorable regarding this criterion [
112,
120].
Employee perception (C14) implies the ability to adopt a new alternative, which assumes employees’ awareness of the acceptance of new technologies. Alternatives that are more frequently used are mainly based on modifying current (traditional) ones and are more accepted by employees [
120].