who inspired us all and shared his valuable experiences in the border of academia and industry and cannot be with us today to see the final result of this joint effort.

Energy-intensive industries can take advantage of process flexibility to reduce operating costs by optimal scheduling of production tasks. In this study we develop a MILP formulation to extend a continuous-time model with energy-awareness to optimize the daily production schedules and the electricity purchase including the load commitment problem. The sources of electricity that are considered are purchase on volatile day-ahead markets, time-of-use (TOU) contracts and base load contracts, as well as onsite generation. The possibility to sell electricity back to the grid is also included. The model is applied to the melt shop section of a stainless steel plant. Due to the large-scale nature of the combinatorial problem which prevents the solution of a monolithic model to nearoptimality, we propose a bi-level heuristic algorithm to tackle instances of industrial size. Case study scenarios show that the potential impact of high prices in the day-ahead markets of electricity can be mitigated by jointly optimizing the production schedule and the associated net electricity consumption cost.

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The notion of Internet of Things (IoT), as well as related topics such as Cyber-Physical Systems, Industrie 4.0 and Smart Manufacturing are currently attracting a lot of attention within the process and manufacturing industries. Clearly, IoT offers many potential applications for automation, ranging from engineering installation of new plants to production management and more intelligent maintenance schemes including novel sensor technologies. The focus of this paper is, however, on the control and operations. Most likely IoT leads to new system architectures where open standards play a significant role. Through better connectivity, information will be much more easily available, which could result in that previously isolated functions will become more closely integrated.Here modeling at the right level of fidelity will be absolutely key. It can be expected that the importance of optimization will increase and this paper discusses some aspects related to the opportunities, challenges and changes triggered by IoT.

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