Purpose -The purpose of this paper is to identify the shortcomings of traditional cost accounting techniques in lean companies and then it seeks to analyse the validity and convenience of value stream costing (VSC) as a tool in a company that has adopted some concepts of lean manufacturing. Design/methodology/approach -The paper reviews the relevant literature in order to discuss the deficiencies of costing methods in lean manufacturing. It evaluates the requirements of VSC and provides a concrete illustration of VSC in the continuous improvement process of a point of sales terminal assembly line. Findings -The paper evidences the possible mistakes of cost accounting. The necessity and validity of VSC in lean manufacturing are presented, followed by a case example. In order to make continuous improvement decisions, VSM, VSC and box score offer complete information on the performance of the value stream. Research limitations/implications -Although accompanied by an application on a real case study, this is not an empirical investigation on the adoption of VSC. Practical implications -VSC requirements agree with the fundamentals of lean management. Therefore, VSC is a valid tool for lean companies, although the applicability depends on the maturity of the lean implementation. Originality/value -This paper contributes to the lean accounting literature because the management accounting literature still lags behind the lean transformation. This is one of the first papers on VSC in relevant journals and the first one to combine VSC and box scores with value stream mapping. The paper will be useful to academics involved in new accounting systems but also to practitioners who are implementing lean manufacturing.

Purpose -Since lean manufacturing considers that "Inventory is evil", the purpose of this paper is to find and quantify the relations between work-in-process inventory (WIP), manufacturing lead time (LT) and the operational variables they depend upon. Such relations provide guidelines and performance indicators in process management. Design/methodology/approach -The authors develop equations to analyse how, in discrete deterministic serial batch processes, WIP and LT depend on parameters like performance time (of each workstation) and batch size. The authors extend those relations to processes with different lots and the authors create a multiple-lot box score. Findings -In this paper, the relations among WIP, LT and the parameters they depend on are derived. Such relations show that when WIP increases, LT increases too, and vice versa, and the parameters they depend on. Finally, these relations provide a framework for WIP reduction and manufacturing LT reduction and agree with the empirical principles of lean manufacturing. Research limitations/implications -Quantitative results are only exact for discrete deterministic batch processes without any delays. Expected results might not be achieved in real manufacturing environments. However, qualitative results show the underlying relations amongst variables. Different expressions might be derived for other situations. Practical implications -Understanding the relations between manufacturing variables allows operations managers better design, implement and control manufacturing processes. The box score, implemented on a spreadsheet, allows testing the effect of changes in different operational parameters on the manufacturing LT, total machine wait time and total lot queue time. Originality/value -The paper presents a discussion about process performance based on the mutual influence between WIP and LT and other variables. The relation is quantified for the discrete deterministic case, complementing the models that exist in the literature. The box score allows mapping more complex processes.

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While multi-model assembly lines are used by advanced lean companies because of their flexibility (different models of a product are produced in small lots and reach the customers in a short lead time), most of the extant literature on how to staff assembly lines focuses either on single-model lines or on mixed-model lines. The literature on multi-model lines is scarce and results given by current methods may be of limited applicability. In consequence, we develop a procedure to staff multi-model assembly lines while taking into account the principles of lean manufacturing. As a first approach, we replace the concepts of operation time and desired cycle time by their reciprocal magnitudes workload and capacity, and we define the dimensionless term of unit workload (load/capacity ratio) in order to avoid magnitudes related to time such as cycle time because, in practice, they might not be known. Next, we develop the necessary equations to apply this framework to a multi-model line. Finally, a piece of software in Python is developed, taking advantage of Google’s OR-Tools solver, to achieve an optimal multi-model line with a constant workforce and with each workstation performing the same tasks across all models. Several instances are tested to ensure the performance of this method.