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Integrated Production System on Social Manufacturing: A Simulation Study

Integrated Production System on Social Manufacturing: A Simulation Study Today, the manufacturing industry must adapt to dynamic customer needs, changing from time to time following market trends. So that the production process in manufacturing requires adjustments, one of which is by forming social manufacturing. This study aims to create an integrated production system model based on social manufac- turing, which involves several Socialized Manufacturing Resources (SMR) as manufacturing resources that are socialized to produce a product. The methods used are field observation, literature study, design of a social man- ufacturing-based production system model, model simulation using ProModel software, and analysis of model simulation results. In this study, the simulation involves four SMRs, each of which makes a part that has been given specifications by the manufacturer based on customer requests. The product produced is the Sanitation Chamber, which is equipped with a control system to monitor reading data via the internet. The model simulation uses the Pro Model software and analyzes resource use, location utilization, and resource costs. Key words: social manufacturing, integrated production systems, simulation study, ProModel INTRODUCTION rapid development of the internet and information technol- Manufacturing systems, information and management tech- ogy today [7], interaction, and information between service nology, and manufacturing's social environment have devel- providers and communities have become easier [8]. On the oped rapidly in recent years. It has changed a lot, such as in- other hand, time-varying customer demands and production creasing global market competition, diversity of customer disruptions force manufacturers to increase flexibility in the demands, and so on [1]. Currently, the manufacturing indus- production process [2]. try is required to meet customer needs that are very diverse Social manufacturing involves stakeholders, customers who and can change at any time and follow specific trends [2]. The access products/services via the internet, social manufactur- Industrial Age 4.0 allows the production system to increase ing resources (SMR), and applications used through social flexibility in making a product customized according to cus- media or applications on mobile devices [6, 9]. As a new form tomer needs [3], commonly referred to as product personal- of manufacturing, social manufacturing shows the complex- ization [4]. Mass personalization of products with diverse ity between social-cyber, as the source of manufacturing ser- customer needs and dynamic online market trends have en- vices is social. Doing so can exacerbate uncertainty and dy- couraged manufacturers to have various manufacturing ca- namic supply services [10]. The merger of the Cyber-Physical pabilities, especially those that appear for personalization or System (CPS) with social media produces a social manufac- innovative products [3]. But sustainable investment to meet turing and basic theory for production organizations in the these needs is too large and not profitable for producers' future [11, 12]. At the core of social manufacturing, three as- strategic development [2]. Many companies implement an pects are configuration, operation, and management per- outsourcing/crowdsourcing system to reduce operating spectives, which are expected to transform production costs to react quickly to dynamic markets [5, 6]. With the modes and social innovation [6]. Social manufacturing is pro- posed as an innovative manufacturing solution for product © 2022 Author(s). This is an open access article licensed under the Creative Commons BY 4.0 (https://creativecommons.org/licenses/by/4.0/) M. W. SARI et al. – Integrated Production System on Social Manufacturing… 231 personalization customization [1, 13]. Besides, social manu- LITERATURE REVIEW facturing is considered to realize "from mind to product" to Social Manufacturing Concept meet customer demand. The future challenge is to add ap- Social Manufacturing is a special production process based plications and the prospect of personalized products and ser- on outsourcing and crowdsourcing [5], manufacturing ser- vices for customers [14]. The social manufacturing commu- vices based on mass socialization in independent organiza- nity is formed to meet every customer need by grouping tions, and service orientation towards the mass individuali- small industries according to resources. Every request from zation paradigm [21, 23]. Social Manufacturing mode inte- customers can be resolved together [15]. Product costs and grates mass personalization on manufacturing, information delivery time are indicators for allocating product orders in interconnection, and product services [15]. Many advanced the social manufacturing community that has been formed manufacturing modes have been proposed in recent years, [16]. and the multitude of providers, being one of the most visible Facing the challenge of mass demand for product personali- changes. Development on Flexible Manufacturing [24, 25], zation, the manufacturing model has developed into social Cloud Manufacturing [1], Manufacturing Grid [26], Collabo- manufacturing [15], where stakeholders who have manufac- rative Manufacturing [27, 28], Networked Manufacturing turing resources share, for example, small medium-size en- [29], and Virtual Enterprise [30, 31, 32], which emphasize col- terprises (SMEs), logistics service providers, and factory laboration and interconnection between manufacturers. The warehouse providers [17], forming a community, referred to manufacturing community consists of many prosumers who as SMR [18, 19], based on social media collaborating with share the same interests and tasks in a social manufacturing manufacturers to produce a product [20]. system. Different users can outsource or add specific tasks Many SMEs and individuals have sprung up with socialized from the relevant manufacturing community according to resources and participated in different segments [21]. The their needs or abilities and then form a virtual manufacturing small and medium industrial community provides various environment or solutions to complete the manufacturing service-oriented capabilities to meet customer demands tasks that result in a product [21]. All manufacturing commu- [22]. The trend of small and medium industrial communities nities involved in the entire life cycle will support social com- forming new communities to produce a product has changed puting, service-oriented technology, and advanced compu- the paradigm of manual and automatic manufacturing sys- ting technology [33]. Multiple manufacturing resources and tems and production modes [12]. This study aims to design capabilities are virtualized and collected to proactively push an integrated production system model based on social man- into demand knowledge-based using social computing and ufacturing, then simulate the existing model using Pro Model service-oriented technology. However, there are differences software. This integrated production system model involves in the manufacturing process, including resource type, re- several SMEs, which form a social manufacturing system and source integration, resource sharing, sharing production co- produce a medical device, namely the Sanitation Chamber, ordination, resource management, product life cycle infor- to prevent the transmission of COVID-19. mation sharing, information technology used, and their char- acteristics, as shown in Table 1. Table 1 The comparison of manufacturing paradigms Flexible Virtual Manufacturing Cloud Collaborative Networked Social Items Manufacturing Enterprise Grid Manufacturing Manufacturing Manufacturing Manufacturing [24, 25] [30, 31, 32] [26] [1, 34] [27, 28] [29] [15, 16, 21] Socialized Type Manufacturing Manufacturing Enterprises Enterprises Enterprises Enterprises manufacturing of resources resources resources resources (SMRs) Manufacturing re- Manufacturing re- Manufacturing Manufacturing Manufacturing Integration Information Resources form sources, data/in- sources, computing resources resources resources and of resources and process product life cycle formation, etc. resources, etc. and abilities and abilities abilities Sharing of resource and Within Among several Among mass enter- Among several Based Among several Among the whole coordination an enterprise enterprises prises enterprises on grid enterprises society of production Semi-decentrali- Management Semi-decentra- Centralized Centralized Centralized Centralized Centralized zed, self-organi- of resources lized zed The Life cycle of product Inter-enterprise Based Information Partially sharing Partially sharing Partially sharing Full-scale sharing and information sharing on grid sharing sharing The Social net- Cloud computing, work, cloud Information Computer-aided ICT, concurrent Grid computing, WAN IoT, RFID, sensor net- Internet computing, technology-enabled technology engineering agent, web service environment work, etc. big data, industry 4.0, etc. Flexibility, agility, Flexibility, agility, Flexibility, agility, re- Flexibility, Flexibility, Manufacturing Flexibility, based Agility, resource resource sharing, value-added source sharing, resource information Characteristics on modularity sharing, efficiency on-demand, service, social cost-saving sharing sharing value-added service innovation 232 Management Systems in Production Engineering 2022, Volume 30, Issue 3 Socialized Manufacturing Resource Socialized Manufacturing Research (SMR) is a resource owned by stakeholders in social manufacturing systems, such as small-medium enterprises (SMEs), smart facto- ries, logistics service providers, and public warehouse pro- viders, forming a social media-based community with pro- ducers to collaborate to produce products [2]. With the development of the mobile internet and social networks, interaction and sharing of information among service pro- viders have become more accessible. Social manufactur- ing is interrelated by a contractual relationship between the manufacturer and its partners, while the production sequence relationships are built among SMR providers [16, 35]. Many SMRs with decentralized, adaptive, and Fig. 1 Social Manufacturing system design self-organizing characteristics began to group as commu- nities to provide specialized manufacturing services to In the design of this social manufacturing system, there prosumers [36]. SMR communities are complex, dynamic are two production processes, namely the component autonomous systems to co-create individualized products production process at SMR and the final product produc- and services [6]. tion process at the Integrator. Each SMR involved already has a supplier for component manufacturing materials RESEARCH METHODS following the specifications required to manufacture The methods used in this study were conducting field ob- product components. After each SMR component is com- servations, literature studies, designing a social manufac- pleted, they are then sent to the Integrator for the assem- turing system model, testing the system, and analyzing bly process into the final product. Furthermore, the final the test results. Field observations carried out by the re- product will be brought to the distributor to be marketed search team are essential to determine the development to the market. of the spread of COVID-19. The observation process that has been carried out is by looking at data on the internet System Model Simulation about the story of the COVID-19 pandemic, the use of the The social manufacturing system model simulation was Sanitation Chamber to prevent virus transmission, and carried out using the ProModel software, with the steps which locations have used the Sanitation Chamber. presented in Fig. 2. This research takes a case study on an integrated produc- tion process based on social manufacturing to produce a medical device in a Sanitation Chamber. During this pan- demic, the need for medical devices in a sanitation cham- ber is urgently needed to prevent COVID-19 transmission. As demand increases, production can be carried out quickly and distributed to various public service facilities. Based on this background, this research will develop a so- cial manufacturing-based sanitation chamber production system involving SMRs. Field observations and literature studies have been carried out and involved several SMRs. The following process compiles a social manufacturing system model and then simulates the model using Pro- Model software. System Design The design of the social manufacturing system in this study is presented in Fig. 1, which involves four SMRs to make a product. Each SMR makes the components that make up the product, according to the specifications pro- vided by the Manufacturer. After each component is ready, it is then sent to the integrator for the installation and assembly process. Fig. 2 System model simulation flowchart M. W. SARI et al. – Integrated Production System on Social Manufacturing… 233 The first step is to create a model of the social manufac- The process of designing and installing components in turing system in the ProModel software. Then, input data each SME can be done in parallel, so there is no waiting for the social manufacturing system, such as the number for one of the components to be completed. The initial of SMRs involved, the assumption of working hours per process starts with the Center for Energy Studies (PSE). day, the cost required to make a part for each SMR and We design an integrated production system to produce a the placement of the SMR locations, because it will deter- Sanitation Chamber, starting from selecting SMEs, device mine the transportation costs. Furthermore, the simula- design, what raw materials are needed, and what costs tion can be done through the Run button on the Pro- are required, including the estimated total time needed to Model, and then the results can immediately be seen on make this product. Then, we sent the device image's de- the monitor in the form of tables and graphs. sign to the SMEs involved being executed immediately. PT The simulation results in the form of graphs can be seen ATMI makes the body frame for the Sanitation Chamber immediately after the Run process. Furthermore, the sim- using stainless steel base material to ensure that this de- ulation results are analyzed to obtain appropriate re- vice can last longer and be easier to clean. In making this search data, then documented. body frame, PT ATMI took about two weeks. For infor- mation, that PT ATMI has good competence in terms of RESULTS AND DISCUSSION making frames. PT ATMI's business location is in Solo, The difference between the social manufacturing system Central Java, about 64 km from Yogyakarta. Therefore, in this study and Ding's research is the social manufactur- communication and coordination are carried out via ing system model. In research conducted by [2], a social WhatsApp and mobile phones. manufacturing system was created by involving several Furthermore, CV Bisri designed the sprayer installation on SMRs with far apart locations, to produce printer ma- the body frame by the specifications of the drawings. The chines. Each SMR completes a part then is continued and production process of this sprayer takes about a week. combined by the next SMR until the product is finished Then, the sprayer components were brought to PSE for and returned to the manufacturer. In this study, the sim- the integration process with the body frame. CV Alfan car- ulation involves four SMRs, each of which makes a part ried out the control system's design and installation ac- that has been given specifications by the manufacturer cording to the specifications we have provided. The con- based on customer requests. The product produced is the trol system that has been completed is then brought to Sanitation Chamber, which is equipped with a control sys- PSE to be assembled and integrated with other parts. All tem to monitor reading data via the internet. hardware requirements were met, then the device was In this simulation study, four SMRs produced a Sanitation built and integrated with other components. Quality con- Chamber, namely PT ATMI, CV Bisri, CV Alfan, and CV trol is also carried out to test the feasibility of the devices Ekrar. PT ATMI is tasked with making body frames made that have been made. To monitor the results of tempera- from stainless steel, and CV Bisri is in charge of designing ture measurements at the Sanitation Chamber, an An- and installing the sprayer, CV Alfan is in order of designing droid-based application was created by CV Ekrar so that and installing the controller. CV Ekrar is in charge of de- the results can be watched anywhere. The simulation re- veloping an internet of things (IoT) based monitoring sys- sults using Pro Model software are presented in Table 2. tem application. The system model that has been made is Table 2 presents data on the scheduled time for each pro- presented in Fig. 3. Each SMR designs product compo- duction process in hours (HR). The average time it takes nents at their respective locations, then after the compo- to complete the product is 252.70 hours. The body nents are finished, they are assembled and integrated frame's design and installation process have the highest with other parts at the PSE. We got all information about load time, which takes 528 hours. The lowest load time is the production process, such as material supplier, produc- in the fine-tuning and rejecting warehouse processes, tion time, and production costing, through field observa- which is 114 hours. Percent Empty means the percentage tions and in-depth interviews with the owners. of the production system actively. The smaller the per- centage value, meaning that the system does a lot of work in a specific time, and vice versa if the percentage value is higher, it indicates that the system is idle. Percent Occu- pied shows the level of use of each part in an integrated production system. In Table 2, it is shown that the highest percentage level of use is 90.04% in the body frame man- ufacturing process, and the lowest level of use is 3.72% in the sprayer installation process. There are four entities in this integrated production process, namely controller, sprayer, IoT application, and body frame. Fig. 3 Social Manufacturing System Model 234 Management Systems in Production Engineering 2022, Volume 30, Issue 3 Table 2 The results of Location States Multi from Pro Model software Controller Supplier (1) 165.03 65.4441 34.56 0 0 Sprayer Supplier (2) 114.69 95.30382 4.7 0 0 IoT Application 114.69 95.30382 4.7 0 0 Fig. 5 Simulation results for Entity States Supplier (3) Raw Material 354 17.28993 82.71 0 0 Furthermore, location utilization in an integrated produc- Supplier (4) tion system is presented in Fig. 6. The highest location uti- Design Installation 1 234 41.10704 52.49 6.399003 0 lization is 59.78% for design and installation 3 (IoT appli- Design Installation 2 180 60.26455 3.72 36.01706 0 cation), while the lowest is 0.88% for fine-tuning. Design Installation 3 318 24.67805 24.6 50.72544 0 Design Installation 4 528 9.956708 90.04 0 0 Quality Control 1 304 22.76002 77.24 0 0 Quality Control 2 306 21.25817 70.9 7.843137 0 Quality Control 3 456 10.63074 84.1 5.274123 0 Quality Control 4 314.1 23.62305 76.38 0 0 Assembly Installation 146 74.10959 25.89 0 0 Fine Tunning 114 94.73684 5.26 0 0 Final Quality Control 222 35.13514 64.86 0 0 Distributor 318 25.25157 74.75 0 0 Market 127.5 100 0 0 0 Reject Warehouse 114 100 0 0 0 Fig. 6 Location Utilization Joint 1 2 510 5.676471 94.32 0 0 The use of resources for transporters and inspectors con- Joint 3 4 114 94.47368 5.53 0 0 sists of the number of units, scheduled time (hour), num- ber of times used, average time per usage (minutes), av- The simulation results for each entity's activities are pre- erage time travel to use (minutes), as shown in Fig. 7. sented in Fig. 4, which shows the system's current quality, the average time in the system, the average time in move logic, average time waiting, the average time in operation, and average time blocked. The average time in the system is 28965 minutes. Fig. 7 Resources simulation results The use of resources for transporters and inspectors con- Fig. 4 Simulation results for Entity Activity sists of the number of units, scheduled time (hour), num- ber of times used, average time per usage (minutes), av- The average time in move logic is 11054.03 minutes. The erage time travel to use (minutes), as shown in Fig. 7. The average time waiting is 6 minutes. The average time in op- average value of scheduled time for transporters was eration is 14580 minutes, and the average time block is 189.79 hours, and the average value for inspectors was 3324.97, in the final product BICO-19. Fig. 5 displays entity 202.46 hours. The highest value of Average time per usage states for the controller, sprayer, IoT application, and raw is 1714.29 minutes in raw material of body frame produc- material of body frame, showing the percentages in move tion, and the average time per usage value of all trans- logic, waiting, operation, and block. porters is 535.71 minutes. The average time per usage for The average value of the move logic percentage is 7.98%, inspectors is 1080 minutes. The average time travel to use the waiting percentage is 10.47%, the operation percent- transporters is 53.75 minutes, while for the inspectors, it age is 23.34%, and the blocked percentage is 15.36%. Name Scheduled Time (HR) % Empty % Part Occupied % Full % Down M. W. SARI et al. – Integrated Production System on Social Manufacturing… 235 is 0 minutes because they did not move anywhere. The Most of the production needs were in the body frame's average travel time to park for transporters is 91.59 manufacture because the primary materials used are ex- minutes, while for inspectors, it is 0 minutes because they cellent, made of stainless steel, so the price is high. Mean- do not travel; they only work at the production site. while, for the inspector's cost, the highest value is the in- Furthermore, the percentage of utilization in transporters spector 3, 62.13 USD with a total cost percentage is is 21.79%, and for inspectors is 46.69%. The rate of 10.80%, namely in making IoT applications, which require blocked travel is 0% because overall, the production pro- a lot of services rather than raw materials. This IoT appli- cess is running as planned. The transporter value for the cation is connected to a modem in the control system con- scheduled time on the body frame's raw material is the nected to the internet to access temperature measure- highest, 353.17 hours because the distance from the pro- ment data anywhere. duction location is far from the PSE assembly site. Then, the estimated resource costs for transporters and inspec- CONCLUSION tors are presented in Table 3. Determination of the cost Simulation of an integrated production system model is of each resource in each SME based on the estimated real essential because it can measure the actual system to be needs to produce a sanitation chamber product. The high- built. In this research, a framework design and integrated est percentage of usage cost was 37.43% for the trans- production system model in social manufacturing have in- porter for raw material of body frame, with a total price volved four SMEs in producing a medical device in a sani- of around 180 USD, and the portion of the total cost was tation chamber. Based on the literature [2, 6, 35], in this 31.29%. social manufacturing-based production system, reaching an agreement between the manager and the SMEs in- Table 3 volved is carried out by direct discussion and communica- Resource costing tion so that all tasks are carried out based on the trust of each stakeholder. The total time needed to produce a san- itation chamber is around 30 days, with eight working hours per day, so the working hour is not counted as com- plete 24 hours. In this research, only model design and simulation were carried out. Through the production of Transpor- this Sanitation Chamber, it is hoped that it can reduce the ter risk of transmission of the COVID-19 virus. As discussed in Controller Nicola's research, the transmission of the COVID-19 virus cannot be avoided [37], but at least we can minimize its Transpor- transmission by using masks, spraying disinfectants, using ter Sprayer sanitation chambers, etc. Some things can still be im- proved for further study with different methods, such as Transpor- making optimization using mathematical models, discuss- ter ing production cost problems, and the effectiveness of IoT SMEs' involvement in social manufacturing systems. Re- Application searchers can also compare conventional production sys- Transpor- tems (non-social manufacturing) in factories with an inte- ter grated production system based on social manufacturing. Raw Material ACKNOWLEDGMENT This research was funded by The 2020 Research Grant Inspector 1 from The Department of Mechanical and Industrial Engi- neering, Faculty of Engineering, Universitas Gadjah Mada, Yogyakarta Indonesia. Inspector 2 REFERENCES [1] F.T.Y. Cheng and L.Z.A.Y.C. Nee, “Advanced manufacturing systems : socialization characteristics and trends,” J. Intell. Manuf., vol. 28, no. 5, pp. 1079-1094, 2017, doi: Inspector 3 10.1007/s10845-015-1042-8. [2] K. Ding, P. Jiang, and S. Su, “RFID-enabled social manufacturing system for inter-enterprise monitoring and dispatching of integrated production and transportation Inspector 4 tasks,” Robot. Comput. Integr. Manuf., vol. 49, no. July 2017, pp. 120-133, 2018, doi: 10.1016/j.rcim.2017.06.009. 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Surg., System: A Survey and Perspective,” 2018, doi: vol. 78, no. April, pp. 185-193, 2020, doi: 10.3390/machines6020023. 10.1016/j.ijsu.2020.04.018. Marti Widya Sari ORCID ID: 0000-0003-4462-5259 Universitas Gadjah Mada Universitas PGRI Yogyakarta Jl. Grafika No. 2, Sinduadi, Mlati, Sleman, Yogyakarta 55284, Indonesia e-mail: marti.widya.sari@mail.ugm.ac.id Herianto ORCID ID: 0000-0001-5993-3540 Universitas Gadjah Mada Jl. Grafika No. 2, Sinduadi, Mlati, Sleman, Yogyakarta 55284, Indonesia e-mail: herianto@ugm.ac.id IGB Budi Dharma ORCID ID: 0000-0002-0002-4729 Universitas Gadjah Mada Jl. Grafika No. 2, Sinduadi, Mlati, Sleman, Yogyakarta 55284, Indonesia e-mail: budi.dharma@ugm.ac.id Alva Edy Tontowi ORCID ID: 0000-0002-1083-8961 Universitas Gadjah Mada Jl. Grafika No. 2, Sinduadi, Mlati, Sleman, Yogyakarta 55284, Indonesia e-mail: alvaedytontowi@ugm.ac.id http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Management Systems in Production Engineering de Gruyter

Integrated Production System on Social Manufacturing: A Simulation Study

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de Gruyter
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© 2022 Marti Widya Sari et al., published by Sciendo
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2450-5781
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10.2478/mspe-2022-0029
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Abstract

Today, the manufacturing industry must adapt to dynamic customer needs, changing from time to time following market trends. So that the production process in manufacturing requires adjustments, one of which is by forming social manufacturing. This study aims to create an integrated production system model based on social manufac- turing, which involves several Socialized Manufacturing Resources (SMR) as manufacturing resources that are socialized to produce a product. The methods used are field observation, literature study, design of a social man- ufacturing-based production system model, model simulation using ProModel software, and analysis of model simulation results. In this study, the simulation involves four SMRs, each of which makes a part that has been given specifications by the manufacturer based on customer requests. The product produced is the Sanitation Chamber, which is equipped with a control system to monitor reading data via the internet. The model simulation uses the Pro Model software and analyzes resource use, location utilization, and resource costs. Key words: social manufacturing, integrated production systems, simulation study, ProModel INTRODUCTION rapid development of the internet and information technol- Manufacturing systems, information and management tech- ogy today [7], interaction, and information between service nology, and manufacturing's social environment have devel- providers and communities have become easier [8]. On the oped rapidly in recent years. It has changed a lot, such as in- other hand, time-varying customer demands and production creasing global market competition, diversity of customer disruptions force manufacturers to increase flexibility in the demands, and so on [1]. Currently, the manufacturing indus- production process [2]. try is required to meet customer needs that are very diverse Social manufacturing involves stakeholders, customers who and can change at any time and follow specific trends [2]. The access products/services via the internet, social manufactur- Industrial Age 4.0 allows the production system to increase ing resources (SMR), and applications used through social flexibility in making a product customized according to cus- media or applications on mobile devices [6, 9]. As a new form tomer needs [3], commonly referred to as product personal- of manufacturing, social manufacturing shows the complex- ization [4]. Mass personalization of products with diverse ity between social-cyber, as the source of manufacturing ser- customer needs and dynamic online market trends have en- vices is social. Doing so can exacerbate uncertainty and dy- couraged manufacturers to have various manufacturing ca- namic supply services [10]. The merger of the Cyber-Physical pabilities, especially those that appear for personalization or System (CPS) with social media produces a social manufac- innovative products [3]. But sustainable investment to meet turing and basic theory for production organizations in the these needs is too large and not profitable for producers' future [11, 12]. At the core of social manufacturing, three as- strategic development [2]. Many companies implement an pects are configuration, operation, and management per- outsourcing/crowdsourcing system to reduce operating spectives, which are expected to transform production costs to react quickly to dynamic markets [5, 6]. With the modes and social innovation [6]. Social manufacturing is pro- posed as an innovative manufacturing solution for product © 2022 Author(s). This is an open access article licensed under the Creative Commons BY 4.0 (https://creativecommons.org/licenses/by/4.0/) M. W. SARI et al. – Integrated Production System on Social Manufacturing… 231 personalization customization [1, 13]. Besides, social manu- LITERATURE REVIEW facturing is considered to realize "from mind to product" to Social Manufacturing Concept meet customer demand. The future challenge is to add ap- Social Manufacturing is a special production process based plications and the prospect of personalized products and ser- on outsourcing and crowdsourcing [5], manufacturing ser- vices for customers [14]. The social manufacturing commu- vices based on mass socialization in independent organiza- nity is formed to meet every customer need by grouping tions, and service orientation towards the mass individuali- small industries according to resources. Every request from zation paradigm [21, 23]. Social Manufacturing mode inte- customers can be resolved together [15]. Product costs and grates mass personalization on manufacturing, information delivery time are indicators for allocating product orders in interconnection, and product services [15]. Many advanced the social manufacturing community that has been formed manufacturing modes have been proposed in recent years, [16]. and the multitude of providers, being one of the most visible Facing the challenge of mass demand for product personali- changes. Development on Flexible Manufacturing [24, 25], zation, the manufacturing model has developed into social Cloud Manufacturing [1], Manufacturing Grid [26], Collabo- manufacturing [15], where stakeholders who have manufac- rative Manufacturing [27, 28], Networked Manufacturing turing resources share, for example, small medium-size en- [29], and Virtual Enterprise [30, 31, 32], which emphasize col- terprises (SMEs), logistics service providers, and factory laboration and interconnection between manufacturers. The warehouse providers [17], forming a community, referred to manufacturing community consists of many prosumers who as SMR [18, 19], based on social media collaborating with share the same interests and tasks in a social manufacturing manufacturers to produce a product [20]. system. Different users can outsource or add specific tasks Many SMEs and individuals have sprung up with socialized from the relevant manufacturing community according to resources and participated in different segments [21]. The their needs or abilities and then form a virtual manufacturing small and medium industrial community provides various environment or solutions to complete the manufacturing service-oriented capabilities to meet customer demands tasks that result in a product [21]. All manufacturing commu- [22]. The trend of small and medium industrial communities nities involved in the entire life cycle will support social com- forming new communities to produce a product has changed puting, service-oriented technology, and advanced compu- the paradigm of manual and automatic manufacturing sys- ting technology [33]. Multiple manufacturing resources and tems and production modes [12]. This study aims to design capabilities are virtualized and collected to proactively push an integrated production system model based on social man- into demand knowledge-based using social computing and ufacturing, then simulate the existing model using Pro Model service-oriented technology. However, there are differences software. This integrated production system model involves in the manufacturing process, including resource type, re- several SMEs, which form a social manufacturing system and source integration, resource sharing, sharing production co- produce a medical device, namely the Sanitation Chamber, ordination, resource management, product life cycle infor- to prevent the transmission of COVID-19. mation sharing, information technology used, and their char- acteristics, as shown in Table 1. Table 1 The comparison of manufacturing paradigms Flexible Virtual Manufacturing Cloud Collaborative Networked Social Items Manufacturing Enterprise Grid Manufacturing Manufacturing Manufacturing Manufacturing [24, 25] [30, 31, 32] [26] [1, 34] [27, 28] [29] [15, 16, 21] Socialized Type Manufacturing Manufacturing Enterprises Enterprises Enterprises Enterprises manufacturing of resources resources resources resources (SMRs) Manufacturing re- Manufacturing re- Manufacturing Manufacturing Manufacturing Integration Information Resources form sources, data/in- sources, computing resources resources resources and of resources and process product life cycle formation, etc. resources, etc. and abilities and abilities abilities Sharing of resource and Within Among several Among mass enter- Among several Based Among several Among the whole coordination an enterprise enterprises prises enterprises on grid enterprises society of production Semi-decentrali- Management Semi-decentra- Centralized Centralized Centralized Centralized Centralized zed, self-organi- of resources lized zed The Life cycle of product Inter-enterprise Based Information Partially sharing Partially sharing Partially sharing Full-scale sharing and information sharing on grid sharing sharing The Social net- Cloud computing, work, cloud Information Computer-aided ICT, concurrent Grid computing, WAN IoT, RFID, sensor net- Internet computing, technology-enabled technology engineering agent, web service environment work, etc. big data, industry 4.0, etc. Flexibility, agility, Flexibility, agility, Flexibility, agility, re- Flexibility, Flexibility, Manufacturing Flexibility, based Agility, resource resource sharing, value-added source sharing, resource information Characteristics on modularity sharing, efficiency on-demand, service, social cost-saving sharing sharing value-added service innovation 232 Management Systems in Production Engineering 2022, Volume 30, Issue 3 Socialized Manufacturing Resource Socialized Manufacturing Research (SMR) is a resource owned by stakeholders in social manufacturing systems, such as small-medium enterprises (SMEs), smart facto- ries, logistics service providers, and public warehouse pro- viders, forming a social media-based community with pro- ducers to collaborate to produce products [2]. With the development of the mobile internet and social networks, interaction and sharing of information among service pro- viders have become more accessible. Social manufactur- ing is interrelated by a contractual relationship between the manufacturer and its partners, while the production sequence relationships are built among SMR providers [16, 35]. Many SMRs with decentralized, adaptive, and Fig. 1 Social Manufacturing system design self-organizing characteristics began to group as commu- nities to provide specialized manufacturing services to In the design of this social manufacturing system, there prosumers [36]. SMR communities are complex, dynamic are two production processes, namely the component autonomous systems to co-create individualized products production process at SMR and the final product produc- and services [6]. tion process at the Integrator. Each SMR involved already has a supplier for component manufacturing materials RESEARCH METHODS following the specifications required to manufacture The methods used in this study were conducting field ob- product components. After each SMR component is com- servations, literature studies, designing a social manufac- pleted, they are then sent to the Integrator for the assem- turing system model, testing the system, and analyzing bly process into the final product. Furthermore, the final the test results. Field observations carried out by the re- product will be brought to the distributor to be marketed search team are essential to determine the development to the market. of the spread of COVID-19. The observation process that has been carried out is by looking at data on the internet System Model Simulation about the story of the COVID-19 pandemic, the use of the The social manufacturing system model simulation was Sanitation Chamber to prevent virus transmission, and carried out using the ProModel software, with the steps which locations have used the Sanitation Chamber. presented in Fig. 2. This research takes a case study on an integrated produc- tion process based on social manufacturing to produce a medical device in a Sanitation Chamber. During this pan- demic, the need for medical devices in a sanitation cham- ber is urgently needed to prevent COVID-19 transmission. As demand increases, production can be carried out quickly and distributed to various public service facilities. Based on this background, this research will develop a so- cial manufacturing-based sanitation chamber production system involving SMRs. Field observations and literature studies have been carried out and involved several SMRs. The following process compiles a social manufacturing system model and then simulates the model using Pro- Model software. System Design The design of the social manufacturing system in this study is presented in Fig. 1, which involves four SMRs to make a product. Each SMR makes the components that make up the product, according to the specifications pro- vided by the Manufacturer. After each component is ready, it is then sent to the integrator for the installation and assembly process. Fig. 2 System model simulation flowchart M. W. SARI et al. – Integrated Production System on Social Manufacturing… 233 The first step is to create a model of the social manufac- The process of designing and installing components in turing system in the ProModel software. Then, input data each SME can be done in parallel, so there is no waiting for the social manufacturing system, such as the number for one of the components to be completed. The initial of SMRs involved, the assumption of working hours per process starts with the Center for Energy Studies (PSE). day, the cost required to make a part for each SMR and We design an integrated production system to produce a the placement of the SMR locations, because it will deter- Sanitation Chamber, starting from selecting SMEs, device mine the transportation costs. Furthermore, the simula- design, what raw materials are needed, and what costs tion can be done through the Run button on the Pro- are required, including the estimated total time needed to Model, and then the results can immediately be seen on make this product. Then, we sent the device image's de- the monitor in the form of tables and graphs. sign to the SMEs involved being executed immediately. PT The simulation results in the form of graphs can be seen ATMI makes the body frame for the Sanitation Chamber immediately after the Run process. Furthermore, the sim- using stainless steel base material to ensure that this de- ulation results are analyzed to obtain appropriate re- vice can last longer and be easier to clean. In making this search data, then documented. body frame, PT ATMI took about two weeks. For infor- mation, that PT ATMI has good competence in terms of RESULTS AND DISCUSSION making frames. PT ATMI's business location is in Solo, The difference between the social manufacturing system Central Java, about 64 km from Yogyakarta. Therefore, in this study and Ding's research is the social manufactur- communication and coordination are carried out via ing system model. In research conducted by [2], a social WhatsApp and mobile phones. manufacturing system was created by involving several Furthermore, CV Bisri designed the sprayer installation on SMRs with far apart locations, to produce printer ma- the body frame by the specifications of the drawings. The chines. Each SMR completes a part then is continued and production process of this sprayer takes about a week. combined by the next SMR until the product is finished Then, the sprayer components were brought to PSE for and returned to the manufacturer. In this study, the sim- the integration process with the body frame. CV Alfan car- ulation involves four SMRs, each of which makes a part ried out the control system's design and installation ac- that has been given specifications by the manufacturer cording to the specifications we have provided. The con- based on customer requests. The product produced is the trol system that has been completed is then brought to Sanitation Chamber, which is equipped with a control sys- PSE to be assembled and integrated with other parts. All tem to monitor reading data via the internet. hardware requirements were met, then the device was In this simulation study, four SMRs produced a Sanitation built and integrated with other components. Quality con- Chamber, namely PT ATMI, CV Bisri, CV Alfan, and CV trol is also carried out to test the feasibility of the devices Ekrar. PT ATMI is tasked with making body frames made that have been made. To monitor the results of tempera- from stainless steel, and CV Bisri is in charge of designing ture measurements at the Sanitation Chamber, an An- and installing the sprayer, CV Alfan is in order of designing droid-based application was created by CV Ekrar so that and installing the controller. CV Ekrar is in charge of de- the results can be watched anywhere. The simulation re- veloping an internet of things (IoT) based monitoring sys- sults using Pro Model software are presented in Table 2. tem application. The system model that has been made is Table 2 presents data on the scheduled time for each pro- presented in Fig. 3. Each SMR designs product compo- duction process in hours (HR). The average time it takes nents at their respective locations, then after the compo- to complete the product is 252.70 hours. The body nents are finished, they are assembled and integrated frame's design and installation process have the highest with other parts at the PSE. We got all information about load time, which takes 528 hours. The lowest load time is the production process, such as material supplier, produc- in the fine-tuning and rejecting warehouse processes, tion time, and production costing, through field observa- which is 114 hours. Percent Empty means the percentage tions and in-depth interviews with the owners. of the production system actively. The smaller the per- centage value, meaning that the system does a lot of work in a specific time, and vice versa if the percentage value is higher, it indicates that the system is idle. Percent Occu- pied shows the level of use of each part in an integrated production system. In Table 2, it is shown that the highest percentage level of use is 90.04% in the body frame man- ufacturing process, and the lowest level of use is 3.72% in the sprayer installation process. There are four entities in this integrated production process, namely controller, sprayer, IoT application, and body frame. Fig. 3 Social Manufacturing System Model 234 Management Systems in Production Engineering 2022, Volume 30, Issue 3 Table 2 The results of Location States Multi from Pro Model software Controller Supplier (1) 165.03 65.4441 34.56 0 0 Sprayer Supplier (2) 114.69 95.30382 4.7 0 0 IoT Application 114.69 95.30382 4.7 0 0 Fig. 5 Simulation results for Entity States Supplier (3) Raw Material 354 17.28993 82.71 0 0 Furthermore, location utilization in an integrated produc- Supplier (4) tion system is presented in Fig. 6. The highest location uti- Design Installation 1 234 41.10704 52.49 6.399003 0 lization is 59.78% for design and installation 3 (IoT appli- Design Installation 2 180 60.26455 3.72 36.01706 0 cation), while the lowest is 0.88% for fine-tuning. Design Installation 3 318 24.67805 24.6 50.72544 0 Design Installation 4 528 9.956708 90.04 0 0 Quality Control 1 304 22.76002 77.24 0 0 Quality Control 2 306 21.25817 70.9 7.843137 0 Quality Control 3 456 10.63074 84.1 5.274123 0 Quality Control 4 314.1 23.62305 76.38 0 0 Assembly Installation 146 74.10959 25.89 0 0 Fine Tunning 114 94.73684 5.26 0 0 Final Quality Control 222 35.13514 64.86 0 0 Distributor 318 25.25157 74.75 0 0 Market 127.5 100 0 0 0 Reject Warehouse 114 100 0 0 0 Fig. 6 Location Utilization Joint 1 2 510 5.676471 94.32 0 0 The use of resources for transporters and inspectors con- Joint 3 4 114 94.47368 5.53 0 0 sists of the number of units, scheduled time (hour), num- ber of times used, average time per usage (minutes), av- The simulation results for each entity's activities are pre- erage time travel to use (minutes), as shown in Fig. 7. sented in Fig. 4, which shows the system's current quality, the average time in the system, the average time in move logic, average time waiting, the average time in operation, and average time blocked. The average time in the system is 28965 minutes. Fig. 7 Resources simulation results The use of resources for transporters and inspectors con- Fig. 4 Simulation results for Entity Activity sists of the number of units, scheduled time (hour), num- ber of times used, average time per usage (minutes), av- The average time in move logic is 11054.03 minutes. The erage time travel to use (minutes), as shown in Fig. 7. The average time waiting is 6 minutes. The average time in op- average value of scheduled time for transporters was eration is 14580 minutes, and the average time block is 189.79 hours, and the average value for inspectors was 3324.97, in the final product BICO-19. Fig. 5 displays entity 202.46 hours. The highest value of Average time per usage states for the controller, sprayer, IoT application, and raw is 1714.29 minutes in raw material of body frame produc- material of body frame, showing the percentages in move tion, and the average time per usage value of all trans- logic, waiting, operation, and block. porters is 535.71 minutes. The average time per usage for The average value of the move logic percentage is 7.98%, inspectors is 1080 minutes. The average time travel to use the waiting percentage is 10.47%, the operation percent- transporters is 53.75 minutes, while for the inspectors, it age is 23.34%, and the blocked percentage is 15.36%. Name Scheduled Time (HR) % Empty % Part Occupied % Full % Down M. W. SARI et al. – Integrated Production System on Social Manufacturing… 235 is 0 minutes because they did not move anywhere. The Most of the production needs were in the body frame's average travel time to park for transporters is 91.59 manufacture because the primary materials used are ex- minutes, while for inspectors, it is 0 minutes because they cellent, made of stainless steel, so the price is high. Mean- do not travel; they only work at the production site. while, for the inspector's cost, the highest value is the in- Furthermore, the percentage of utilization in transporters spector 3, 62.13 USD with a total cost percentage is is 21.79%, and for inspectors is 46.69%. The rate of 10.80%, namely in making IoT applications, which require blocked travel is 0% because overall, the production pro- a lot of services rather than raw materials. This IoT appli- cess is running as planned. The transporter value for the cation is connected to a modem in the control system con- scheduled time on the body frame's raw material is the nected to the internet to access temperature measure- highest, 353.17 hours because the distance from the pro- ment data anywhere. duction location is far from the PSE assembly site. Then, the estimated resource costs for transporters and inspec- CONCLUSION tors are presented in Table 3. Determination of the cost Simulation of an integrated production system model is of each resource in each SME based on the estimated real essential because it can measure the actual system to be needs to produce a sanitation chamber product. The high- built. In this research, a framework design and integrated est percentage of usage cost was 37.43% for the trans- production system model in social manufacturing have in- porter for raw material of body frame, with a total price volved four SMEs in producing a medical device in a sani- of around 180 USD, and the portion of the total cost was tation chamber. Based on the literature [2, 6, 35], in this 31.29%. social manufacturing-based production system, reaching an agreement between the manager and the SMEs in- Table 3 volved is carried out by direct discussion and communica- Resource costing tion so that all tasks are carried out based on the trust of each stakeholder. The total time needed to produce a san- itation chamber is around 30 days, with eight working hours per day, so the working hour is not counted as com- plete 24 hours. In this research, only model design and simulation were carried out. Through the production of Transpor- this Sanitation Chamber, it is hoped that it can reduce the ter risk of transmission of the COVID-19 virus. As discussed in Controller Nicola's research, the transmission of the COVID-19 virus cannot be avoided [37], but at least we can minimize its Transpor- transmission by using masks, spraying disinfectants, using ter Sprayer sanitation chambers, etc. Some things can still be im- proved for further study with different methods, such as Transpor- making optimization using mathematical models, discuss- ter ing production cost problems, and the effectiveness of IoT SMEs' involvement in social manufacturing systems. Re- Application searchers can also compare conventional production sys- Transpor- tems (non-social manufacturing) in factories with an inte- ter grated production system based on social manufacturing. Raw Material ACKNOWLEDGMENT This research was funded by The 2020 Research Grant Inspector 1 from The Department of Mechanical and Industrial Engi- neering, Faculty of Engineering, Universitas Gadjah Mada, Yogyakarta Indonesia. Inspector 2 REFERENCES [1] F.T.Y. Cheng and L.Z.A.Y.C. Nee, “Advanced manufacturing systems : socialization characteristics and trends,” J. Intell. Manuf., vol. 28, no. 5, pp. 1079-1094, 2017, doi: Inspector 3 10.1007/s10845-015-1042-8. [2] K. Ding, P. Jiang, and S. Su, “RFID-enabled social manufacturing system for inter-enterprise monitoring and dispatching of integrated production and transportation Inspector 4 tasks,” Robot. Comput. Integr. Manuf., vol. 49, no. July 2017, pp. 120-133, 2018, doi: 10.1016/j.rcim.2017.06.009. 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Journal

Management Systems in Production Engineeringde Gruyter

Published: Sep 1, 2022

Keywords: social manufacturing; integrated production systems; simulation study; ProModel

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