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|title=WITPO: A System for Tracking and Optimization of Work-in-Progress Inventory
|pdfUrl=https://ceur-ws.org/Vol-3692/paper8.pdf
|volume=Vol-3692
|authors=Jānis Grabis,Jānis Kampars,Rūta Pirta-Dreimane,Edgars Mendziņš,Inga Laksa
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==WITPO: A System for Tracking and Optimization of Work-in-Progress Inventory==
https://ceur-ws.org/Vol-3692/paper8.pdf
WITPO: A System for Tracking and Optimization of Work-in-
Progress Inventory
Jānis Grabis1,∗,†, Jānis Kampars1,†, Rūta Pirta-Dreimane1,†, Edgars Mendziņš2,† and
Inga Laksa3,†
1 Riga Technical University, Zunda krastmala 10, Riga 1048, Latvia
2 Dati Group, Balasta dambis 80A, Riga 1048, Latvia
3 Will Sensors, Kaivas iela 33 k-2 – 67, Riga 1021, Latvia
Abstract
Manufacturing companies have embraced Internet of Things and data analytical technologies to
optimize manufacturing processes. In a typical case, they benefit from having a controlled
environment with well-structured workflows and established facility layouts. However,
production of highly customized products and organization of shop-floor operations remains a
challenge. This project investigates the problem of work-in-progress inventory management in
the case of on-demand production of customized products having a multitude of production
workflow variants and a significant share of human operations. It aims to create an information
system, which uses Internet of Thing to track movement of work-in-progress inventory and
optimizes materials picking and placement. The computer vision is used to reduce the need for
materials tagging and spatial database technologies are used to create a dynamic view of the
shop-floor layout taking into account current locations of work-in-progress inventory. The
system can be customized for various manufacturing facilities. The project is carried out in a
university industry collaboration involving companies specializing in industrial Internet of
Things. The system is tested at a medium-sized printing company.
Keywords
Industry 4.0, Internet of Things, work-in-progress inventory, process optimization 1
1. Introduction
Large manufacturing companies have achieved a high degree of automation in running of
their operations courtesy of integration between Enterprise resource planning (ERP) and
Manufacturing execution systems (MES) [1]. However, information systems used by small
and medium size companies often lack sophistication of the advanced systems or do not
have sufficient scale to invest in complex digital technologies [2]. Current developments in
information technology allow smaller companies to deploy modularized solutions for
RPE@CAiSE’24: Research Projects Exhibition at the International Conference on Advanced Information Systems
Engineering, June 3–7, 2024, Limassol, Cyprus
∗ Corresponding author.
† These authors contributed equally.
grabis@rtu.lv (J. Grabis); janis.kampars@rtu.lv (J. Kampars); ruta.pirta-dreimane@rtu.lv (R. Pirta-
Dreimane); edgars.mendzins@datigroup.com (E. Mendziņš); inga@willsensors.lv (I. Laksa)
0000-0003-2196-0214 (J. Grabis); 0000-0003-0045-5593 (J. Kampars); 0000-0001-8568-0276 (R. Pirta-
Dreimane)
© 2024 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
60
CEUR
ceur-ws.org
Workshop ISSN 1613-0073
Proceedings
specific value-added process [3]. This project specifically considers the problem of Work-
in-Progress (WIP) Inventory Management (IM) at a printing company. WIP inventory are
materials and intermediate products stored on the shop floor close to manufacturing
equipment to await the next production step. The materials are picked up to set up the next
production step, and intermediate products obtained as the result of the production step
are placed at a suitable location for further processing. These operations can be performed
at different levels of automation. Technologies such as Radio-frequency identification
(RFID) are often used to facilitate the WIP management operations [4]. The problem at
hands is characterized by on-demand production, material and location tagging restrictions,
large-product variety, limited WIP inventory storage space and dynamics shop-floor layout
(i.e., pick-up routes are affected by the current placement of WIP inventory).
The project goal is to develop a modular and extensible system to optimize WIP IM for
custom on-demand manufacturing processes. The novel features of the system are 1)
combination of Internet of Things including computer vision to track movement of WIP
inventory, 2) dynamic representation of the layout of manufacturing facilities and 30
optimization methods to generate optimal WIP inventory pick-up routes and suggests
placement of the intermediate products on the shop-floor. It is ought to be integrated with
the core enterprise resources planning system and the sensing infrastructure established
could be used for optimization of other manufacturing processes including digital twin
development. The project furthers the field of information systems engineering by co-
designing intelligent data processing system and optimal decision-making algorithms with
balanced allocation of computations between edge and cloud computing. This paper reports
the current results with focus on requirements elicitation and high-level architectural
design. The project furthers
The project is carried out by consortium of Riga Technical University and two
information technology consulting companies as well as by a printing company providing
testing facilities. The project is funded as a part the Competence Centre of Information and
Communication Technologies program in Latvia what fosters implementation of innovation
projects in industry. The rest of the paper is organized as follows. Section 2 reviews related
work on warehouse management. The overall project information is provided in Section 3.
Business process analysis is presented in Section 4. Section 5 introduces the architecture of
the WIP IM system and Section 6 concludes.
2. Related Work
The WIP IM optimization system referred as to WITPO is developed on the basis of the state-
of-the-art of computer augmented warehouse management. There is a large number of
inventory and warehouse management processes such as materials receiving, placement,
storage, picking, packing and shipping [5, 6], and this project addresses warehouse layout
planning, information availability, location planning and routing to pick-up materials.
Empirical evidence suggests that material pick-up is one of the most time-consuming
operations [7], and real-time data are need for efficient routing [8]. RFID tags are the most
commonly used materials tracking technology, and it requires tagging materials
themselves, pallets, trolleys or tracking gates [9]. The overall materials tracking and
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operations management systems has the following components: IoT component for data
gathering, data processing module for identifications of materials, planning module and
execution module [10]. Further research [11] supplements these components with a
machine learning component to analyze custom movement trajectories taken by production
operations. Edge devices such as self-guided carts use infra-red light to avoid collisions and
RFID for tracking [12]. The MQTT protocol ensures moderate data exchange reliability of
80%. IoT technologies are often used in smart shopping to identify products and their
movement [13]. A closely related study [14] focuses on digitalization of printing processes
and proposes a business process management approach to optimize the manufacturing
processes. Robots are used to perform manufacturing steps and AGV are used to pick-up
materials. The technologies are deployed in a laboratory environment and both advantages
and shortcomings are assessed.
The current methods are well suited for materials identification and pick-up routes
optimization in facilities with regular layout. The WITPO project focuses on facilities with
irregular layout, which dynamically changes.
3. Project Plan and Partnership
The project follows a waterfall approach. This approach is selected because the project was
proceeded by a feasibility study. The feasibility study established key requirements and
proposed high level design of the envisioned solution. The project concerns WIP IM in the
production environment. A production operator receives information about production
orders what includes a list of materials required to produce an end-product. Sensing
technologies such as computer vision and RFID provide data on location of the materials.
These data are aggregated and processed to create a materials pick-up route, which is
executed to set-up a production step. The production step yields an intermediate product,
which should be placed in suitable location on the shop-floor for the next production step.
The current project consists of: 1) Requirements and design phase; 2) Implementation
phase; and 3) Field testing phase. The project is relatively short (one and half years) and
every phase is six months long. The system design was performed using the C4 method (see
section 5). This method is well-suited to develop modularized systems and to allocate work
to partners responsible for specific functionality. The project is carried out by four partners:
1) Riga Technical university – an academic partner responsible for the overall design and
optimization; 2) Will Sensors – an industry partner working in the area of industrial IoT and
responsible for development of object identification techniques; 3) Data Group – an
industry partner developing edge-cloud solution and responsible for the system integration
and deployment; and 4) A printing company – participates in defining requirements and
provides facilities for the field study. The implementation phase includes two parallel traits,
namely, a) development of WIP inventory optimization model; and b) implementation of
the platform services. The implementation and field testing leads to the TRL7 level. Testing
is carried out in a test environment and several iterations are envisioned to tune accuracy
of sensing technologies. The final evaluation will be performed at the printing company’ s
facilities. It will focus on accuracy of identification of materials as well as efficiency of WIP
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IM. It is aimed to strike a balance between investment in sensing equipment and
performance gains in IM.
4. Business Processes Analysis
To define WIP process optimization areas, the case company is investigated. Existing
business processes were defined, along with the potential improvement areas.
Consequently, the initial requirements to the WITPO system were defined.
4.1. Case Company
The project is motivated and will be tested by the needs of a case company, a small and
medium size printing company (further referred as JTI). The company specializes in
printing of high quality books, diaries, advertisements and similar products. The number of
books printed was 4.5 mill. in 2020. The company has about 155 employees. The company
performs an end-to-end printing process on paper sheets. The state-of-the-art computer
controlled machinery is used in the production. Still, the process requires continuous
supervision by workers and a certain number of manual operations. The workers' skills and
performance significantly affect production efficiency and quality. During the study,
researchers analyzed the company’s production processes as well as interviewed
production managers and information technology specialists and conducted field visits.
There are 900-1000 WIP items on any given day. The IM system supports registration of
components of unfinished products and finished products. Operators have difficulties to
locate the WIP items and to locate the most suitable location for newly arriving product
component palettes. The aim is to reduce the time operators spend on non-value-added
operations such as locating WIP items and most suitable free storage spots and to determine
the optimal placement of WIP palettes.
4.2. Existing business processes
JTI existing inventory and warehouse management processes were analyzed, using field
observation and semi-structured interviews methods. The analysis encompassed two
business processes observation visits in the JTI manufacturing premises. In the first visit,
preliminary processes were discussed and drafted. The open questions were identified and
discussed in the second visit of the JTI. Afterwards the final business processes diagrams
were prepared. The primary activities of the process involve receiving orders from
customers, preparing manufacturing plans, gathering materials, production, and managing
the location and movement of materials and WIP.
The primary roles engaged in the process include the project manager, planner,
operator, warehouse agent and laborer. The project manager is the primary contact point for
the customers, they discuss the order, agree on delivery dates and register the information
into the system for planning. The planner is responsible for the orders collection and
manufacturing plan preparation for each machine. The plan is prepared for 1-2 days and
might be changed on a daily basis. The operator performs work on the manufacturing
facilities. The warehouse agent is in charge about materials issuing and record keeping.
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While the laborer is engaged in various support tasks, such as assisting with assembly or
production processes, handling materials and others. One of the main responsibilities of the
laborer is to move and re-move inventory, considering the available space in the
manufacturing facility and the locations of subsequent processing machines. WIP
movement and re-movement can be performed several times per day.
While observing and analyzing business processes, several potential areas for
improvement were identified. (1) Low value adding and time-consuming activities in the
movement of WIP inventory. A specific role is designated for inventory movement and re-
movement throughout the day. Time is consumed in locating WIP inventory as WIP location
data is not tracked. (2) Insufficient level of automation and information exchange between
the people, systems and machines of the manufacturing line, for example, produced items,
time spent. (3) Limited data analysis possibilities. The main information is processed in
spreadsheets or even paper form documents, such as notes in the order bags, stickers with
order numbers. Additionally, the order status information is not tracked based on the
available information from the devices. Furthermore, there are no available means to
measure the effectiveness of business processes.
Figure 1: Overview of the JTI manufacturing process.
4.3. Requirements for business process improvement
The business process analysis yields key requirements towards the WITPO system. From a
functional perspective, the system aims to improve production steps (steps S.6. – S.10.
Figure 1). The main focus is on more efficient identification, location and optimal placement
of WIP inventory, resulting in time savings and reduction of low value adding activities
64
(steps S.9., S.12.). According to the interview with the JTI representatives, in the high season,
these activities raise significant waste [15], including waiting, non-utilized potential, motion
and extra processing. The requirements are defined as user stories and appropriately
prioritized. Besides the functional requirements, WITPO non-functional requirements have
been defined, considering the common software quality criteria such as functionality
stability, performance effectiveness, reliability, maintainability and others.
5. Technical Architecture
The technical architecture is developed using the C4 method following the gradual
elaboration starting with the landscape diagram (level 0) to component diagrams (level 3),
which could be furthered during the detailed design. The landscape diagram (Figure 2)
shows all key systems relevant to the WIP IM. The WITPO is created as a cloud-edge
computing system. The WITPO portal is a central cloud-based system providing access to
the core functionality. The edge system is responsible for locating materials. Edge devices
such as cameras and RFID tags provide raw positioning data. The WITPO portal interacts
with the external ERP system, which manages production orders and provide information
to WIP IM. The context diagram (referred as to Level 1 in C4) zooms in on a particular
system of interest. It is created for the WITPO portal and the edge system separately (not
shown). The context diagrams are further elaborated using container diagrams (level 2).
Figure 2: The landscape diagram of the WITPO system.
A container is a separately runnable/deployable unit that executes code or stores data
[16]. The Container diagram (not included in the paper) shows the high-level software
architecture and distribution of responsibilities. It also shows the major technology choices
and how the containers communicate with one another. There are two major points of
interaction: 1) Web application accessed using mobile devices by shop-floor operators; and
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2) GIS based desktop application for production managers. The key feature of the WITPO
solution is representation of the dynamic layout of production facilities caused by
placement of the WIP inventory. The data management sub-system is responsible for spatial
data management and dynamic regeneration of the current layout. It also provides a
possibility to determine distances between points on the shop-floor needed for the
optimization algorithm at the database level. The users can view the current positioning of
the WIP inventory what is provided by the indoor positioning system. The optimization and
routing subsystem generates inventory pick-up routes and suggests placement of
intermediate products obtained in manufacturing process. These are displayed to the
production operator using the web application accessed using mobile devices. The
integration sub-system facilitates data exchange between other systems including
production order data exchange with the external ERP system and WIP inventory
movement data store in the data management subsystem.
Every container defined in the container diagram is further elaborated in the component
diagram. For instance, the Web application has the map component displaying a spatial
representation of the production facilities. It shows both static (i.e., manufacturing
equipment) and dynamic (i.e., WIP inventory) objects. The Inventory search and pickup
routing component helps the operators to locate inventory and delivers instructions for
efficient pickup of the required materials. The Inventory placement component displays
recommended inventory placement locations after completing the manufacturing step.
6. Conclusion
The paper introduces an industry-university collaboration innovation project developing a
new system for WIP IM. The main distinctive features of the proposed system are inventory
pick-up routing and placement with respect to dynamic spatial representation of the
production shop-floor, distribution of analytical features between edge and cloud nodes and
utilization of computer vision to minimize tagging of materials. These features allow to use
the system for on-demand production in production facilities having irregular and
dynamically changing shop-floor layouts as well as to extend system for various
applications relaying on sensing and real-time data processing.
The project is currently in its requirements and design phase. The requirements analysis
shows that both current research and practice focus on isolated treatment of WIP IM.
However, a more holistic approach considering integration with other production
processes and IT infrastructure management might yield further performance
improvements. The C4 design method is used in this phase. That allows creating a modular
system, and implementation activities can be allocated to responsible parties. The
evaluation in the field testing phase will focus on finding the right balance between
materials identification accuracy as needed for accurate routing and investment made in
the sensing infrastructure. The computer vision will be prioritized because of its greater
flexibility and traditional RFID technologies will be used as supplementary tools to improve
the accuracy.
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Acknowledgements
The research leading to these results has received funding from the project "Competence
Centre of Information and Communication Technologies" of The Recovery and Resilience
Facility, contract No. 5.1.1.2.I.0/1/22/A/CFLA/008 signed between IT Competence Centre
and Central Finance and Contracting Agency, Research No. 1.1 " Development of a solution
for tracking and optimizing the location of work-in-progress inventory for complex
production processes to increase the efficiency of the production plant (WITPO)".
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