XMANAI partner spotlight - Whirlpool

Enrica Bosani

Name: Enrica Bosani

Job title: Manufacturing R&D manager

Organization: Whirlpool management EMEA

Bio: Enrica Bosani, electronic engineer in Whirlpool since 1994, started her careers in the factory automation supporting shop floor monitoring and control systems deployment in EMEA factories. After a long period with project management responsibilities in several different functions of the multinational company (Supply Chain, Human resources, product development, marketing and sales, IT, finance and Consumer Services), acquiring a deep knowledge of the company processes at cross functional level, joined EMEA Operations Excellence department in 2017 initially as Industry4.0 program PMO and then, in 2019, as manufacturing R&D manager with the responsibility of the coordination of all EMEA Integrated supply chain initiatives in the funded research programs (Horizon and EIT manufacturing).

Name: Giorgio Pennesi

Job title: Data Scientist

Organization: Whirlpool management EMEA

Bio: Dr. Giorgio Pennesi is a Data Scientist at Whirlpool. He obtained his PhD in Mathematical Models and Methods in Engineering from Politecnico di Milano, Italy, where he performed academic research on the equations describing geophysical phenomena. He then exploited his mathematical background to deal with data engineering and machine learning problems with applications to cyber security, working as software engineer of intelligence platforms. Giorgio joined Whirlpool in 2020. Since then he worked on a variety of machine learning and optimization projects, mainly related to statistical forecast and Natural Language Processing tools, aiming at improving the activity of the supply chain and the consumer service.

Q: What is your organization’s role in XMANAI?

A: The role of Whirlpool EMEA in the XMANAI project is the one of the industrial end user with the accountability to provide competence and expertize for the definition of the business requirements and the validation of the final result. Our contribution also creates evidence on the business impact that has to be addressed by the project outcome which has to be measured in quantitative and qualitative way to support an effective exploitation of the solution. As end users we’re also the potential future customer of the XMANAI platform so we may contribute to the exploitation strategy and to the final evaluation of all the risks and constraints which may affect the transformation of the platform to a commercial solution.

 

Q: How does XMANAI relate with your or your team’s background and interests?

A: Whirlpool is firmly convinced that Artificial Intelligence is one of the most interesting new technologies that, once proficiently introduced in the enterprise processes, may really ensure a strong and sustainable competitive advantage. And yet, the several pilot experiences launched in the past years mainly in manufacturing processes (quality control, production planning, predictive maintenance …) have been affected by a weak adoption by the users with a strong impact on the sustainability in the medium/long term of these type of solution. We’re convinced that this weakness depends from two key factors: the first is the lack of competence related to this specific technology in our organization. In this perspective Whirlpool started initiatives to create dedicated learning paths for its workforce (blue and white collars) to ensure the first level of awareness. The second, and probably more relevant, factor is the lack of users’ trust that often affect these type of solutions, mainly when the result of AI are far or totally contrary to human experience or perception. We’re convinced that the possibility to open the AI black box creating a deeper understanding of the source of the “strange” results may drive to the adoption … and this is just what XMANAI is.

 

Q: What is the novelty of XMANAI and the main benefits envisaged for your organization?

A: The main novelty driven by XMANAI is for Whirlpool the possibility to ensure its users to deeply understand the result of an AI system, creating the proper level of trust which may affect the human decisions. For us, the AI applications will always have a “Human in the loop” approach as the system has to be considered always as a support to human decision making process. To affect the human decision we’ve to change the people mindset, proofing that not only AI may ensure a reliable prediction, data driven, but may also be an effective support to human understanding of the complexity: in this perspective the AI is replacing humans but is a real enabler for workforce empowering.

 

Q: Which target groups can benefit from XMANAI?

A: Whirlpool brings in the project a use case focused on sales demand forecasting for a D2C (Direct To Consumer) market, targeting the possibility to get out of XMANAI not only a reliable sales forecast but also the possibility of a deeper understanding of the demand dynamics. The target group identified, that has been engaged in the project, is constituted by the Supply Chain central roles, accountable for demand forecasting management at EMEA level, and the sales and marketing roles, accountable for the market strategy definition and execution. XMANAI project also highlighted an important gap in Whirlpool EMEA IT organization, addressing a stakeholder’s role (data engineer), with specific responsibilities and accountabilities, which at the moment doesn’t exist but has to be created for a sustainable introduction of these systems.