In this paper, an innovative framework to apply Value Stream Mapping to products with complex Bill of Materials is presented. Value Stream Mapping is one of the best tools to map a process and to identify its main criticalities. Unfortunately, it can be effectively applied to linear systems only. When the manufacturing process is complex with flows merging together, Value Stream Mapping cannot be used straightforwardly. Thus, the main objective of this work is to solve this limitation so that lean production can be enhanced in complex systems too. The proposed approach is based on seven iterative steps and integrates Value Stream Mapping with other tools typical of industrial engineering. The basic idea is to execute a preliminary analysis to identify the ‘critical production path’ using the Temporized Bill of Material. Then, improvements are made considering all possible sharing with other secondary paths as possible constraints. Once the critical path has been optimized, a new path may become critical. Thus, the analysis proceeds iteratively until the optimum is reached and the Work In Process level has decreased under a desired value. A case study taken from a real setting environment is finally presented to assess the validity of the methodology proposed here.

In this article, two alternative approaches to include variability analysis in value stream mapping (VSM) are presented. Notoriously, VSM is one of the best tools to map a process and to identify its main criticalities in order to enhance lean manufacturing. Unfortunately, in the standard approach, data are recorded on the map as deterministic, disregarding the real variability of the process. This is a strong limit because, especially within manufacturing processes, variability has a significant impact on costs and leads to several wastes. Therefore, it must be carefully analysed and reduced before lean manufacturing can be set into place. To overcome this weakness, this article proposes two alternative approaches based on statistics and fuzzy algebra, respectively. Both methods are designed to support practitioners and can be easily applied to several industrial applications. Their practicality is finally demonstrated through an industrial application of relevance. Obtained results are compared and respective advantages/disadvantages are presented and discussed.

The present paper proposes a modified version of the Manufacturing cost deployment (MCD) method to analyse engineer-to-order (ETO) production systems. The novel approach, named Project cost deployment (PCD), introduces two substantial and innovative modifications. To begin with, the concept of manual assembly macro-activity replaces the traditional concept of station. Then, a brand-new structure for classifying and analysing losses is introduced, that is specifically defined to deal with the inefficiencies of the manual assembly tasks. The validity of the approach is proved by a real-world industrial application. The obtained results demonstrate that the PCD method allows the analyst to identify the hidden losses and to quantify the wastes from an economical point of view. In addition, PCD permits to estimate the impacts of potential (lean) improvement activities and projects in terms of both efficiency and effectiveness.