Smart Domain: Smart Manufacturing

The Strategic Decision Area (SDA) assigned is “Maintenance,” based on the views of various students who reflected on how Critical Systems Heuristics (CSH) and systems thinking can enhance the understanding and management of operational complexities. Students have shared their insights on how these approaches can help manage the complexities of operations. Based on the analysis of Pre -Course Survey findings and group talks, it is evident that maintenance is viewed as a crucial element in guaranteeing the seamless operation of organizational activities, prioritizing the improvement of processes, increasing effectiveness, and simplifying workflows via digital transformation. Student Perspectives on Maintenance: Understanding maintenance from the students’ perspectives reveals that it is not just about fixing or preserving systems but involves aligning operational objectives with strategic goals. For example, Monica discusses the importance of digital technologies in modernizing mining operations, which directly influences maintenance by making processes more efficient and cost-effective. Similarly, Maxwell’s view ties maintenance to data-driven decision-making, where scheduling and resource allocation are optimized through digital solutions. Role of Maintenance in Digital Transformation: Maintenance, as and SDA also plays a crucial part in aiding digital transformation initiatives in various industries. It guarantees that all operational systems stay operational, trustworthy, and flexible to change, which is especially important within the group’s overall focus on “digitizing operations.” One example is when a student pointing out how automating the value chain can improve operational efficiency by integrating maintenance with digital tools, which reduces errors and allows resources to focus on strategic tasks. Bidirectional Influence of Maintenance and Digital Operations: Maintenance has a bidirectional impact on the group’s SDA theme, “Maintenance and Digital Operations.” Maintenance practices guarantee that operational continuity and performance are maintained, but the adoption of digital operations is changing how maintenance is carried out. Digital technologies including IoT, automation, and data analytics offer predictive maintenance abilities, enabling companies to tackle possible problems beforehand rather than after they occur. Thus, maintenance upholds operational integrity to support digital transformation, while digitalization improves maintenance by increasing predictability, efficiency, and strategic planning. Scholarly Articles: Recent scholarly articles emphasize the integration of digital tools and advanced methodologies to enhance maintenance practices. Introna and Santolamazza (2024) highlight strategic maintenance planning using digitalization for better asset performance. Dui et al. (2024) focus on optimizing maintenance strategies with AI and IoT. A 2021 review covers various paradigms for selecting maintenance strategies and evaluates how strategic decision-making for maintenance types can impact organizations. A 2021 article outlines developing smart maintenance strategies with digital tools. Thes studies highlights the importance of digital transformation in modernizing maintenance with the goal of improving operational efficiency.

This paper synthesizes how maintenance can influence or is influenced by inventory management for digitalized operations. The integration of maintenance and inventory management plays a key role in increasing & optimizing performance and reducing costs. Digital technologies, such as Cyber-Physical Systems (CPS), the Internet of Things (IoT), and digital twins, make the integration of these two operations management functions feasible and beneficial in any organization. Inventory management is the process of overseeing and controlling the flow of goods in a company. It is a key element in the supply chain, as it allows for inventory tracking from suppliers to manufacturers, warehouses, and retailers. The objective of inventory management is to “have the right products in the right place at the right time” (IBM, n.d.). The efficient and reliable operation of the inventory management process/system is critical to the success of a business. Maintenance management is key to ensuring the reliable operation of the inventory management system. The use of cyber-physical systems and IoT devices enables the real-time monitoring of the status & condition of physical assets and inventory levels. Digital twins provide a digital representation of the physical environment, namely, physical assets, processes and systems. They play an important role in the digitalization of inventory management and maintenance systems. These digital technologies facilitate predictive maintenance and just-in-time inventory management. Digital twins may allow for the simulation of scenarios showing the impact of maintenance activities on inventory management and vice versa. Vatn (2018) highlights the benefits of using digital technologies, namely, improved decision making using real-time data, accurate forecasting and better alignment of inventory and maintenance activities. for inventory and maintenance activities. Inventory management practices influence maintenance operations by ensuring that spares are available timeously when needed for maintenance purposes. This reduces delays within maintenance activities. According to Van Horenbeek et al. (2013), the effectiveness of maintenance linked inventory management practices and minimize downtime. Inventory levels are monitored by continuous review systems that allow for immediate replenishment when inventory levels fall below a predefined limit. This is effective in areas where the demand for spare parts is unpredictable. Within a stable environment, periodic review policies involve ordering inventory at fixed intervals (Van Horenbeek et al., 2013). Conversely, the reliability of inventory management systems is improved by the implementation of age- based and condition-based maintenance strategies using digital technologies that can predict failures and trigger the appropriate maintenance strategy (Vatn, 2018). Age-based maintenance involves replacing parts at predetermined intervals, while condition-based maintenance uses real-time data to perform maintenance only when needed. According to Van Horenbeek et al. (2013), both maintenance strategies benefit from accurate inventory management, as the timely availability of parts is critical to minimizing downtime and ensuring operational efficiency.

The Strategic Decision Area (SDA) assigned is “Maintenance,” based on the views of various students who reflected on how Critical Systems Heuristics (CSH) and systems thinking can enhance the understanding and management of operational complexities. Students have shared their insights on how these approaches can help manage the complexities of operations. Based on the analysis of Pre -Course Survey findings and group talks, it is evident that maintenance is viewed as a crucial element in guaranteeing the seamless operation of organizational activities, prioritizing the improvement of processes, increasing effectiveness, and simplifying workflows via digital transformation. Student Perspectives on Maintenance: Understanding maintenance from the students’ perspectives reveals that it is not just about fixing or preserving systems but involves aligning operational objectives with strategic goals. For example, Monica discusses the importance of digital technologies in modernizing mining operations, which directly influences maintenance by making processes more efficient and cost-effective. Similarly, Maxwell’s view ties maintenance to data-driven decision-making, where scheduling and resource allocation are optimized through digital solutions. Role of Maintenance in Digital Transformation: Maintenance, as and SDA also plays a crucial part in aiding digital transformation initiatives in various industries. It guarantees that all operational systems stay operational, trustworthy, and flexible to change, which is especially important within the group’s overall focus on “digitizing operations.” One example is when a student pointing out how automating the value chain can improve operational efficiency by integrating maintenance with digital tools, which reduces errors and allows resources to focus on strategic tasks. Bidirectional Influence of Maintenance and Digital Operations: Maintenance has a bidirectional impact on the group’s SDA theme, “Maintenance and Digital Operations.” Maintenance practices guarantee that operational continuity and performance are maintained, but the adoption of digital operations is changing how maintenance is carried out. Digital technologies including IoT, automation, and data analytics offer predictive maintenance abilities, enabling companies to tackle possible problems beforehand rather than after they occur. Thus, maintenance upholds operational integrity to support digital transformation, while digitalization improves maintenance by increasing predictability, efficiency, and strategic planning. Scholarly Articles: Recent scholarly articles emphasize the integration of digital tools and advanced methodologies to enhance maintenance practices. Introna and Santolamazza (2024) highlight strategic maintenance planning using digitalization for better asset performance. Dui et al. (2024) focus on optimizing maintenance strategies with AI and IoT. A 2021 review covers various paradigms for selecting maintenance strategies and evaluates how strategic decision-making for maintenance types can impact organizations. A 2021 article outlines developing smart maintenance strategies with digital tools. Thes studies highlights the importance of digital transformation in modernizing maintenance with the goal of improving operational efficiency.

The digitalization of scheduling involves leveraging technologies like artificial intelligence (AI), machine learning (ML), and real-time data analytics to enhance resource management and scheduling efficiency. Digital scheduling automates task assignment and resource allocation, adapting dynamically to changes in operations. This has profound effects on layout strategies, which define how physical and digital resources are organized within an enterprise (Castells, 2000).In manufacturing environments, digital scheduling reduces bottlenecks and optimizes workflows, which impacts layout design by enabling leaner operations. It reduces the need for large inventories and improves equipment utilization, thus minimizing excess space requirements (Ross, 2019). Similarly, in service industries, the use of digital scheduling tools optimizes staff deployment and customer flow, leading to layouts that maximize efficiency and responsiveness (Oludapo et al., 2024). Additionally, digital scheduling creates opportunities for data-driven decisions on layout changes. As organizations gather and analyze data on employee productivity, machine usage, and demand patterns, they can reconfigure layouts to meet evolving operational needs, improving overall flexibility (Merali, 2006). In both physical and digital settings, layouts become more adaptable to real-time changes, enhancing the enterprise’s ability to remain agile. How the Assigned SDA Influences or Is Influenced by the Group SDA (Layout Strategies): Digital scheduling significantly influences layout strategies by driving the need for more flexible, responsive designs. Effective scheduling reduces idle time and improves workflow efficiency, necessitating adaptable layouts that can respond to shifting resource needs (Piccoli et al., 2024). For instance, optimized schedules inform how workstations, equipment, and storage areas should be placed to facilitate smooth operations and minimize downtime. Conversely, the effectiveness of digital scheduling is influenced by the design of the enterprise layout. Poorly designed layouts can reduce the potential benefits of scheduling systems, as inefficient spatial arrangements may hinder workflow optimization. Therefore, there is a reciprocal relationship where digital scheduling enhances layout efficiency, and well-structured layouts allow digital scheduling to perform optimally.

In this paper we will seek to answer the following question, how do capacity constraints influence maintenance in digital operations? Maintenance plays a critical role in ensuring there is a minimal downtime thereby increasing organization capability (Lazakis et al. 2010). Capacity constraints in digital operations are particularly important in formulating maintenance strategies. The constraints may entail technological capabilities, equipment, and workforce to effectively carry out maintenance. The advent of technology has enabled organizations to be able to leverage on the use of digital twin (Dong et al., 2023). Digital twins act as a virtual identical copy of the physical entity enabling the company to quickly predict a fault that may take place on the physical entity. Also, digital enables maintenance teams in testing various scenarios and solutions in a digital environment before rolling on physical assets. Within wind renewable energy industry there is a high importance of ensuring maximum availability of wind turbines yet reducing maintenance cost (Zhang, C., & Yang, T. 2020). Zhang highlights the importance of dynamic scheduling of maintenance to reduce points of failures by changes in the environment. Efficient resource allocation and coordination is important to ensure maintenance tasks are carried out since they require special tools, transport, and qualified technicians. According to Zonta et al. (2020) it is crucial for organizations to promote predictive maintenance instead of breakdown maintenance since maintenance costs account between 15 – 60 % of operational costs. An enabling factor of predictive maintenance is the availability of data which can be harnessed to reduce downtime, maintenance cost and improved operational efficiency. The article by Alsyouf (2007) looks at how maintenance policies can drive productivity and profitability within manufacturing industry. Furthermore, Alysouf highlights maintenance should not only be viewed as a cost center but also as a profit generating activity. This is because maintenance can avert inferior quality production thereby saving the business from financial losses which it may experience. To effectively conduct the academic synthesis, the paper has relied on applied research to solve practical problems relating to capacity constraints on maintenance of digital operations.

This paper explores how the influence of AI in Store layout strategies can lead to the enhanced revenue for Supermarkets in the digital society. The integration of AI technologies, such as machine learning, computer vision, and predictive analytics, allows supermarkets to optimize their store layouts based on detailed consumer behavior insights. Post Covid or Pandemic studies indicate that customers are more willing to travel to the store and are open to good shopping experiences. Recently AI advancements have been studied and their effect on Customer experience. AI can be of use by analysing instore movements and behaviors. Supermarkets can understand how customers navigate aisles, and which products customers pay the most attention to as well as where there are shortfalls and challenges (Nguyen et al., 2022). Supermarkets can create a good customer experience by optimizing the flow of traffic and layout of the store (Nguyen et al., 2022). AI driven insights can help in informing how to place products strategically which increases the convenience for the customer (Nguyen et al., 2022). Real time adjustments can me bade to the layout of stores based on changing consumer patterns and preferences. This is possible during festive holidays and season changes where the needs of customers change and the layout can be tailored to suite the shift in needs (Using AI to Optimize Your Retail Store Layout, 2024). Using AI as a driver of store layout can lead to operational efficiency in terms of inventory management. Products that are only in demand can be source, as well as forecasting periods where a surplus might be needed (AiBoss, 2023). This ensures popular items are always in stock and reduces the chances of lost sales due to being understocked (AiBoss, 2023). AI can lead to personalised shopping experienced due to the utilisation of customer data (Business, 2023). Knowing customer preferences can lead to tailored product recommendations, which further enhances the customer experience, leading to satisfaction and loyalty (Business, 2023). This paper will explore how the application of AI in store layout strategies not only enhances the shopping experience but also drives significant revenue growth for supermarkets. By leveraging AI to understand and predict customer behavior, supermarkets can create more efficient, customer-centric layouts that boost sales and profitability in the digital

In an increasingly interconnected and technology-driven world, the effective management of product maintenance is critical. It’s no longer enough to simply react to breakdowns; instead, companies must proactively ensure operational efficiency, minimize downtime, and extend the lifespan of their products. This is where digitalisation comes in, offering a wide array of tools to revolutionize maintenance practices (Lee et al., 2013). We’re seeing a convergence of technologies like the Internet of Things, cloud computing, and AI, providing unparalleled capabilities for monitoring, analyzing, and optimizing maintenance activities (Schmidt et al., 2015). Think about the traditional model of product maintenance – often reactive, with scheduled checks at fixed intervals, regardless of actual need. This approach is quickly becoming outdated. Digitalisation is bringing in a new era of condition-based and predictive maintenance. By harnessing real-time data and advanced analytics, we can identify potential problems before they even arise (Sterk & Shryock, 1997). This means less downtime, lower maintenance costs, and improved safety, all while using resources more effectively. Simply adopting new technologies isn’t enough; to truly unlock the potential of digitalization in product maintenance, companies need a strategic roadmap that aligns with their broader digital transformation goals (Wixom & Watson, 2001). This involves investing in the right technologies, upskilling their workforce, and cultivating a culture where decisions are driven by data. In today’s competitive landscape, embracing digitalisation is no longer optional, it’s essential for companies to thrive and maintain a competitive edge (Sundararajan, 2017). This paper adopts a systems perspective to explore how a process-based approach can lead to addressing these dilemmas guided by the following research question: “How can digitalization improve product maintenance in its lifecycle? Influence of Assigned SDA on Group SDAA: My assigned SDA, “How can digitalization improve product maintenance in its lifecycle?”, is intrinsically linked to our group’s broader focus on “Maintenance”. Digitalisation acts as a catalyst for effective maintenance strategies, empowering companies to optimize their activities and achieve superior outcomes. By harnessing the power of digital technologies, companies can transform their maintenance practices, leading to increased efficiency, reduced costs, and enhanced product value throughout the entire lifecycle.

Enhancing operational efficiency and guaranteeing asset longevity require the integration of maintenance and reliability as digital operations processes. Reliability is the ability of systems to function consistently over time, whereas maintenance includes a variety of tactics meant to maintain the performance of equipment. Effective work design has a direct impact on these functions by influencing how activities are planned and carried out, which in turn affects overall performance and employee satisfaction. (Parker, 2017). The idea of “Design for Maintenance,” which highlights the significance of integrating maintainability into the product design phase, is a crucial component of maintenance. By making items easy to service and repair, this strategy lowers future maintenance expenses and downtime. Modular designs, for example, improve reliability by enabling the rapid replacement of malfunctioning parts without causing system disruptions. Additionally important is the connection between strategic decision-making and maintenance. Decisions about maintenance plans must be in line with overarching business objectives as businesses work towards operational excellence. Achieving strategic goals including cost reduction, increased productivity, and safety is facilitated by effective maintenance procedures. (Ammad, 2023). By emphasising predictive maintenance strategies that use data analytics to improve decision-making, this alignment guarantees that maintenance operations are both proactive and reactive. Work design plays a crucial role in influencing maintenance decisions. According to Parker, a well-organised workplace encourages employee ownership and participation, which raises job satisfaction and decreases turnover. Employee participation in the design process can help identify possible maintenance issues, which improves the planning and execution of maintenance tasks. Additionally, a well-designed job can reduce monotonous labour that causes burnout, increasing worker reliability in general. In conclusion, thoughtful work design and strategic alignment with organisational goals define the interaction between maintenance and reliability as digital operations functions. Organisations can improve operational efficiency and guarantee long-term asset reliability by emphasising maintainability in product design and creating a motivated workforce through efficient job design.