Decentral decision-making for energy-aware charging of intralogistics equipment

Industrial manufacturing is based on a variety of energy sources, e.g. electricity, oil, and gas. Electricity appears to be particularly relevant to operate most types of industrial production equipment in an environmentally friendly manner. Aside from production machines, intralogistics equipment that performs material handling and supplies processes is a further consumer of electricity in an industrial environment. The integration of electricity-intensive intralogistics equipment has, however, hardly been considered in the research on energy-aware production management. With this paper, we present an optimization model that synchronizes intralogistics charging decisions with a production schedule and the availability of renewable electricity in a power grid. Following the Industrie 4.0-paradigm, we use decentralized decision-making within an agent-based platform that coordinates different types of production and intralogistics equipment. We integrate a forecast signal for the availability of renewable energy into this platform to support an environmentally oriented decision process. In a simulation study that is based on real-world data, we analyze the role of intralogistics handling processes and charging operations with respect to a company's job shop environment and electricity consumption profile. In this simulation, we compare static charging policies in contrast to the proposed optimization model and decentral decision- making under various demand scenarios. The presented approach is shown to be capable of increasing local Logistics Research (2023) 16:4 DOI_ 10.23773/2023_4 electricity consumption in times of peak generation of renewable energy, which contributes to CO2 reductions in industrial manufacturing.