OEE (Overall Equipment Effectiveness) is a widely used indicator in the evaluation of effectiveness of manufacturing systems. However, several authors published alternative approaches for its computation, complicating the implementation step for practitioners. This study analyses the literature regarding OEE, selects four main methodologies for its evaluation and examines the underlying differences between them. A real life case study is analysed to illustrate problems arising during data collection and the differences in results obtained, together with traceable conclusions for improving the performance of production systems, both in traditional and in innovative industrial plants, following Industry 4.0 principles.

Assembly lines managed by means of lean production philosophy are usually characterized by workstations with inline stock areas, supplied by means of items contained in a larger supermarket zone. Furthermore, inline components necessities are usually showed by means of the use of kanbans. In this work, the number of kanbans and the number of carriers serving the line are computed by means of Erlang-C approach, in order to minimize a total cost function obtained as the sum of an estimation of cost of inline stock and of cost of refilling operations. Specifically, the Erlang-C approach is adopted since assures fast re-design of the system when variations in input data occur. Finally, a real-life case study in a company manufacturing items for the automotive market field is presented in order to highlight the approach potentialities when alternative scenarios are studied.

The Overall Equipment Effectiveness (OEE) is a useful tool for evaluating the time that manufacturing resources spend on adding value operations and for idle or waste time, whose elimination or at least whose reduction is progressively recommended. In this paper, four alternative approaches for OEE evaluation are reviewed and commented on in order to guide practitioners in the choice preceding their adoption. Specifically, in accordance with data required for the computation and results assured by the implementation, a preferable operating field is suggested.

The Assembly Line Balancing Problem (ALBP) consists in assigning tasks to operators engaged on a line in such a way that the final item is produced according to a pre-determined production rate and by optimizing pre-defined objective functions. In the literature, a wide range of algorithms claiming to solve ALBP are found, however almost all of them consider this problem from a mathematical standpoint, thus disregarding details which are useful for ensuring the correct implementation of proposed solutions in real-life environments. Authors have gradually narrowed the gap between theory and practice by introducing stochastic operating times when manual operations are executed, or by describing more and more complex versions of the problem, usually known by the term GALBP (Generalized Assembly Line Balancing Problem), where a wide variety of objective functions and constraints are managed. By researching such an area, this paper will investigate the case of redesigning a manufacturing area dedicated to the production of heavy and voluminous items by highlighting the characteristics and peculiarities of the problem. Finally, a real-life case study is solved.

Cathode ray tubes (CRTs) adopted in TV sets and computer monitors represent a consistent portion of waste electrical and electronic equipment (WEEE). In comparison with the recycling of WEEE such as refrigerators or washing machines, the recovery process for CRT containing devices is very difficult. CRTs are composed of four types of glass (panel, funnel, neck and frit seal) with different compositions. Furthermore, dangerous substances are contained within (i.e., lead, barium, strontium and fluorescent dust). Hence, the need to define robust processes for the design and implementation of efficient facilities for CRT cutting arises. This work describes steps guiding the design and the experimental optimal setting of a prototype facility for water-jet cutting of CRTs, in order to obtain recyclable high quality glass. Initially, a version of the cutting facility with manual movement of the cutting tool is set, in order to evaluate expectable cutting results. Subsequently, a detailed setting of automated movement of the cutting tool is carried out, in order to improve the quality of obtainable glass. As a consequence, a water-jet cutting facility which guarantees the cutting of high quality CRTs is finally set and a prototype is implemented.