Francesco Zammori

A new value stream mapping approach for complex production systems

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.

Overall equipment effectiveness of a manufacturing line (OEEML): An integrated approach to assess systems performance

Purpose – Overall equipment effectiveness (OEE) is the key metric to measure the performance of individual equipment. However, when machines operate jointly in a manufacturing line, OEE alone is not sufficient to improve the performance of the system as a whole. The purpose of this paper is to show how to overcome this limitation, by presenting a new metric (overall equipment effectiveness of a manufacturing line – OEEML) and an integrated approach to assess the performance of a line.Design/methodology/approach – An alternative losses classification structure is developed to divide the losses that can be directly ascribed to equipment, from the ones that are spread in the line. Starting from this losses classification structure, an approach based on OEE is developed to evaluate the criticalities and the effectiveness of the line.Findings – This method has been applied to an automated line for engine basements production. Results show that OEEML successfully highlights the progressive degradation of the id...

ANP/RPN: a multi criteria evaluation of the risk priority number

This paper presents an advanced version of the failure mode effects and criticality analysis (FMECA), whose capabilities are enhanced; in that the criticality assessment takes into account possible interactions among the principal causes of failure. This is obtained by integrating FMECA and Analytic Network Process, a multi-criteria decision making technique. Severity, Occurrence and Detectability are split into sub-criteria and arranged in a hybrid (hierarchy/network) decision-structure that, at the lowest level, contains the causes of failure. Starting from this decision-structure, the Risk Priority Number is computed making pairwise comparisons, so that qualitative judgements and reliable quantitative data can be easily included in the analysis, without using vague and unreliable linguistic conversion tables. Pairwise comparison also facilitates the effort of the design/maintenance team, since it is easier to place comparative rather than absolute judgments, to quantify the importance of the causes of failure. In order to clarify and to make evident the rational of the final results, a graphical tool, similar to the House of Quality, is also presented. At the end of the paper, a case study, which confirms the quality of the approach and shows its capability to perform robust and comprehensive criticality analyses, is reported. Copyright

Uncertainty in value stream mapping analysis

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.

Overall equipment effectiveness of a manufacturing line (OEEML)

Purpose – Overall equipment effectiveness (OEE) is the key metric to measure the performance of individual equipment. However, when machines operate jointly in a manufacturing line, OEE alone is not sufficient to improve the performance of the system as a whole. The purpose of this paper is to show how to overcome this limitation, by presenting a new metric (overall equipment effectiveness of a manufacturing line – OEEML) and an integrated approach to assess the performance of a line.Design/methodology/approach – An alternative losses classification structure is developed to divide the losses that can be directly ascribed to equipment, from the ones that are spread in the line. Starting from this losses classification structure, an approach based on OEE is developed to evaluate the criticalities and the effectiveness of the line.Findings – This method has been applied to an automated line for engine basements production. Results show that OEEML successfully highlights the progressive degradation of the id...

Extending value stream mapping: the synchro-MRP case

Nowadays, value stream mapping (VSM) is recognised as the main tool for implementing lean manufacturing. Unfortunately, it always leads to pure pull systems and discourages the adoption of hybrid push/pull ones, although their superiority has been proven in several industrial settings. Due to these issues, this paper presents an enhancement of the standard VSM, which supports the user in designing the future state map of a synchro-MRP system. This new tool includes new mapping icons, simple mathematical formulas and operating guidelines that make it possible to assess the benefits of a synchro-MRP system, with respect to the usual kanban or CONWIP ones. In order to demonstrate the quality and the practical utility of the proposed approach, an industrial application of relevance is finally presented.

A standard agreement for vendor managed inventory

Purpose – The purpose of this paper is to define the standard structure of a vendor managed inventory (VMI) agreement, which can be used as a guideline for the early definition of the agreement.Design/methodology/approach – Starting from an industrial application of relevance, the information flow and the technical details, which are to be defined before the operation startup, are identified and discussed. These data are used as the key points for the definition of the basic frame of the agreement. A particular emphasis is given to the “Technical Specification” and the “Service Level Agreement” sections.Findings – It is shown that a VMI agreement should be arranged into parts dealing with the generic and legal sides of the agreement, whereas the technical aspects and the relation‐specific topics should be addressed in the annexes. This increases the flexibility of the agreement in that, as the VMI relationship evolves over time, changes will affect only the annexes leaving the main body of the agreement u...

Stochastic overall equipment effectiveness

This article focuses on the overall equipment effectiveness (OEE), a key performance indicator typically adopted to support Lean Manufacturing and Total Productive Maintenance. Unfortunately, being a deterministic metric, the OEE only provides a static representation of a process, but fails to capture the real variability of manufacturing performances. To take into account the stochastic nature of the OEE, an approximated procedure based on the application of the Central Limit Theorem is presented: the OEE is considered as a stochastic random variable and its probability density function (pdf) is generated through the aggregation of the pdf of the basic causes of waste. Notwithstanding its approximated nature, the procedure can be applied in most practical cases, since the accuracy is assured provided that the average OEE is lower than 90% and the variability of the losses is high. The validity of the approach has also been confirmed by an industrial application included in this article. The results obtained demonstrate that the stochastic OEE can help in battling variation, for it allows one to identify the hidden losses that account for most of the variability and to estimate the impacts of potential corrective actions in terms of both efficiency and efficacy.

Harmony search algorithm for single-machine scheduling problem with planned maintenance

The single-machine jobs-planned maintenance tasks joint scheduling problem is faced.The machine is subjected to failures with a Weibull distributed time-to-failure.The optimum number of planned maintenance tasks is computed.A specific metaheuristic based on the harmony search algorithm is presented. This paper focuses on the single machine scheduling problem, with sequence dependent setup times. Both processing and setup times are deterministic and the objective is to minimize total earliness and tardiness penalties. The novelty of the model can be traced in the fact that the single machine is subjected to breakdowns and that, in order to increase its availability, planned maintenance tasks are also performed. Hence, jobs and maintenance tasks are jointly considered to find the optimal schedule. These features make the problem NP-hard and so, a quasi-optimal solution is searched using a recent metaheuristic, which integrates harmony search and genetic algorithms. In order to validate the proposed metaheuristic, a comprehensive set of scheduling problems was fully investigated. Obtained results, compared with those of exhaustive (for small problems) and standard metaheuristics, confirm both the robustness and the speed of the proposed approach.

A modified harmony search algorithm for the multi-objective flowshop scheduling problem with due dates

This paper presents a modified harmony search optimisation algorithm (MHSO), specifically designed to solve two- and three-objective permutation flowshop scheduling problems, with due dates. To assess its capability, five sets of scheduling problems have been used to compare the MHSO with a known and highly efficient genetic algorithm (GA) chosen as the benchmark. Obtained results show that the new procedure is successful in exploring large regions of the solution space and in finding a significant number of Pareto non-dominated solutions. For those cases where the exhaustive evaluation of sequences can be applied the algorithm is able to find the whole non-dominated Pareto border, along with a considerable number of solutions that share the same optimal values for the considered optimisation parameters. To validate the algorithm, five sets of scheduling problems are investigated in-depth in comparison with the GA. Results obtained by both methods (exhaustive solutions have been provided as well for small sized problems) are fully described and discussed.