The paper presents a Car Sequencing Problem, widely considered in the literature. The issue considered by the researchers is only a reduced problem in comparison with the problem in real automotive production. Consequently, a newconcept, called Paint Shop 4.0., is considered from the viewpoint of a sequencing problem. The paper is a part of the previously conducted research, identified as Car Sequencing Problem with Buffers (CSPwB), which extended the original problem to a problem in a production line equipped with buffers. The new innovative approach is based on the ideas of Industry 4.0 and the buffer management system. In the paper, sequencing algorithms that have been developed so far are discussed. The original Follow-up Sequencing Algorithm is presented, which is still developed by the authors. The main goal of the research is to find the most effective algorithm in terms of minimization of painting gun changeovers and synchronization necessary color changes with periodic gun cleanings. Carried out research shows that the most advanced algorithm proposed by the authors outperforms other tested methods, so it is promising to be used in the automotive industry.

The relatively limited application of lean in the food process industries has been attributed to

the unique characteristics of the food sector i.e. short shelf-life, heterogeneous raw materials,

and seasonality. Moreover, barriers such as large and inflexible machinery, long setup time,

and resource complexity, has limited the implementation and impact of lean practices in

process industries in general. Contrary to the expectations in the literature, we bring in this

paper a successful experience of lean implementation in a company of the food-processing

sector. By focusing on two lean tools (VSM and SMED), the company reduced changeover

time by 34%, and increased the production capacity of the main production line by 11%.

This improvement enabled the company to avoid the use of temporary workers by extending

the worktime of its workforce during peak months. Moreover, the reduction of setup time

avoided the use of large lot size in production, which, in turn, reduced the total cycle time

of production and the incidence of quality problems.