Principal investigators: B. Vogel-Heuser (TUM), K. Medini (IMT); Other contact person: O. Boissier (IMT)
Short summary and central question
RAMP-UP II project contributes to addressing the limitations of state-of-the-art approaches for agile, resilient and sustainable manufacturing and service industries, in particular in uncertain situations such as crisis context. The focus of the maturation phase is on manufacturing and healthcare services. The main objective of RAMP-UP II is to develop a generic methodology supported by decision-support tools to plan and manage ramp-up and ramp-down projects considering resilience, agility, and sustainability criteria.
Overview of the state-of-the-art
Ramp-up management refers to the value creation phase starting with the completion of product and process design and ending with the achievement of the full production capacity (Schuh et al., 2015; Wochner et al., 2016). This phase plays a crucial role in the successful introduction of products or services into markets. While ramp-up is expected to support flexibility in volume and assortment, it is hindered by several challenges such as complexity of products, services, and production systems. Moreover, this phase is characterized by uncertainty as well as a dynamic environment with mostly untested processes, thus, (positive and negative) risks are high (Ball et al., 2011; Schuh et al., 2015). Recent advances in ramp-up management in product domain involves capacity investment/expansion (Hansen and Grunow 2015; Medini et al. 2020; Pierné et al. 2020; Riffi-Maher and Medini, 2021), product design and functional requirements fulfilment (Kukulies and Schmitt 2018), inventory management and supplier selection (Glock and Jaber 2013), workforce and qualifications (Glock et al. 2012), quality management (Colledani et al. 2018), and information and collaboration (Fjällström et al. 2009).
The COVID-19 sanitary crisis uncovered the difficulty in timely responding to high-volume demands of specific products such as Personal Protective Equipment (EPI) and resuscitative equipment, as well as hospitals capacity. Outsourcing has shown its limitations since the delocalized industry is not performing as expected within the current global crisis (e.g., changing priorities, very tough competition, supply chain disruption). These problems involve not only products but also a variety of services in second and tertiary sectores alike. In the manufacturing domain, spare parts’ shortages affected equipment maintenance services and led to further shortages of products in other markets. Similarly, during the pandemic, healthcare facilities and their related (value) networks undergone critical situations where the demand (patients and equipment) outreaches service capacity and difficult decisions had to be taken. However, looking into the literature, it can be reasonably concluded that service ramp-up and ramp-down and service agility at large have been overlooked compared to product domain (Lenfle and Midler 2009; Christensen 2018; Akkermans et al. 2019). Further on, in both product and service contexts, ramp-up projects often target increasing volumes, speeding up processes, and in some cases improving quality. These targets could only partly support resilience, agility and sustainability and could even be conflicting with these criteria (e.g., useless volume increase, misalignment with market/customer requirements, etc.).
Existing and innovative approaches need to be combined in order to ensure resilient, agile and sustainable value networks at given territorial levels in uncertain environments such as time of crises. For instance, Vogel-Heuser et al. (2020b) proposed model-based engineering for successful management of requirement changes. The proposed method can be extended and combined with other aspects such as resource management to deal with risk management in crises. Furthermore, the proposed BPMN model introduced in (Vogel-Heuser et al., 2020a) for cooperation in working groups and between companies, can be enriched in this project to model and support decision-making processes on a management level in crises. Additionally, existing technologies in Industry 4.0 can be utilized for decision-making and optimization in production. For instance, multi-agent systems (MAS) can increase the decentralization, robustness, 5 flexibility, and autonomy of the production system (Leitão and Karnouskos, 2015; Medini et al., 2021). Therefore, MAS architecture can increase the flexibility during the crisis as well and improve the decisionmaking process. For production optimization, the MAS suggested by Rehberger et al. (2017), Kovalenko et al. (2019) and Medini et al., (2021) can be further extended for production ramp up and ramp down during the crisis. In order to utilize the MAS, Ocker et al. (2019b) introduced a semantic web ontology to facilitate the communication between agents. Ontology as a method for representing and sharing the knowledge of the MAS can be used to model the capabilities of a production system and support the ramp up of new products and services during crises. The current state-of-the-art does not bring sufficient answers to the following general problems:
- How to address service and production ramp-up and ramp-down management?
- How to cover resilience, agility and sustainability criteria when addressing ramp-up?
- How to support ramp-up/ramp-down management with practical decision-support tools?
The teams involved in the project have deep expertise in the relevant topics supporting the successful achievement of the project objectives, which will be introduced in the following.
Objectives of the project
RAMP-UP II will contribute to the following objectives (O):
O1. Development of a ramp-up/ramp-down management approach allowing for resilient and agile value networks, particularly, in uncertain and dynamic environments.
O2. Integrate resilience, agility and sustainability related indicators for planning and managing rampup/ramp-down projects.
O3. Develop decision-support tools allowing to implement and assess alternative collaboration strategies and decentralized decision making in dynamic environments.
O4. Modelling and representation of knowledge about stakeholders involved in value network.
To address these objectives, a multi-disciplinary approach is necessary, combining expertise in industrial management (e.g., O1, O2), multi-agent systems and artificial intelligence (e.g., O3), enterprise modelling, knowledge representation, automation and data management (e.g., O4).
Expected impact on academia, industry and society
Scientific impact :
- Conceptual and methodological contributions in relation to the practices and general guidelines for managing ramp-up/down project in manufacturing and service industries, in particular in uncertain environments, such as crisis context.
- Providing decision-support tools relying on simulation, multi-agent systems and artificial intelligence to assess alternative resilient, agile, and sustainable ramp-up/down strategies.
- Gaining insights into the challenges for building a digital-twin of the value network for real time management of service ramp-up and ramp-down.
Society and industry impacts:
- Improve resilience, agility and sustainability of manufacturing and service industries.
- Reinforce vertical integration of value networks through close collaboration and resource sharing.
- Promote the adoption of decision-support tools relying on simulation, multi-agent systems and artificial intelligence among SMEs and large companies.