The presented article deals with the issue of solving bottlenecks in the logistics flow of a manufacturing company. The Tx Plant Simulation software tool is used to detect bottlenecks and deficiencies in the company’s production, logistics and transportation systems. Together with the use of simulation methods and lean manufacturing tools, losses in business processes are eliminated and consequently flow throughput is improved. In the TX Plant Simulation software environment, using Bottleneck analyzer, bottlenecks were defined on the created simulation model and a method of optimizing logistics flows was designed and tested by introducing the Kanban pull system. This resulted in an improvement and throughput of the entire logistics flow, a reduction in inter-operational stocks and an increase in the efficiency of the production system as a whole.

The aim of most manufacturing and production factories can be defined as achieving smart and sustainable long-term production systems, which means moving towards strategies defined by Zero-Defect Manufacturing strategies with many areas of improvement, such as: lowering overall cost and energy consumption, amount of scrapped output and wasting raw material and improving overall lead times, production status overview, and planning abilities. These facts were the motivations behind the writing of this paper. The authors considered if the classical architecture of Zero-Defect Manufacturing can be improved by additional tools conventionally used in modern manufacturing. The authors have selected Advanced Planning and Scheduling software tools. To prove that different scheduling methods can have a serious impact on overall production results, we prepared a simple case base comparing different scheduling rules. The theoretical basis for writing this manuscript was prepared by studying classical ZDM methodology and defining the industry gap. The methodology is based on the Zero-Defect Manufacturing architecture, which is essential for high-level implementation in industrial practice. Adding new tools, such as Scheduling and the Industrial Internet of Things, to the classic ZDM architecture improves overall methodology. The impact of different scheduling strategies, which is also described in this study, depends on industry and working conditions. The scheduling rules were compared by several key performance indicators, such as lead time and the number of late/unfinished orders. The study realized, with the practical accent shown this challenge, further research in connection with digitalization.

The presented article deals with the application of tools to calculate the Master Production Schedule (MPS) in the production of beverages (consumer packed goods) and its impact on the inventory profile in finite or infinite capacity. The calculation of MPS can be performed at the level of an ERP solution or with dedicated standalone planning software. The first part of the manuscript defines MPS calculations, its position in the planning hierarchy and defines reason of importance having MPS calculations in the consumer product industry. The second part of the article analyses sample data of beverage production, calculates MPS for each item and compares the results of finite/infinite capacity utilization. In the last part of the manuscript, authors discuss if the challenges described in introduction part of the article can be addressed with specific planning solution to calculate MPS.