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Vertical lift module (VLM) is a parts-to-picker system for order picking of small products, which are stored into two columns of trays served by a lifting crane. A dual-bay VLM order picking (dual-bay VLM-OP) system is a particular solution where the operator works in parallel with the crane, allowing higher throughput performance. The purpose of this paper is to define models for different operating configurations able to improve the total throughput of the dual-bay VLM-OP system.

Analytical models are developed to estimate the throughput of a dual-bay VLM-OP. A deep evaluation has been carried out, considering different storage assignment policies and the sequencing retrieval of trays.

A more accurate estimation of the throughput is demonstrated, compared to the application of previous models. Some use guidelines for practitioners and academics are derived from the analysis based on real data.

Differing from previous contributions, these models include the acceleration/deceleration of the crane and the probability of storage and retrieve of each single tray. This permits to apply these models to different storage assignment policies and to suggest when these policies can be profitably applied. They can also model the sequencing retrieval of trays.

In order-picking activities, the performance of the system can be influenced by different variables such as the order to be fulfilled, the distance to be covered or the experience of operators. Usually, this kind of activity is performed by operators rather than machines to assure flexibility. Consequently, their fatigue accumulation can decrease the performance of the overall system. The purpose of this paper is to define the kind of device to be used in an order-picking context, to obtain data which can be utilized for the evaluation of the level of fatigue and to improve the performance of the picking system.

The paper presents a comparison between existing fatigue methods which can be applied in a picking context. In addition, an analysis of the physiological literature for the evaluation of a new device for the monitoring of fatigue level is carried on and its practical use is shown.

The proposed research identifies in the heart rate monitor the device that, thanks to its advantages, can be the best one to be used in an industrial context for monitoring the physical fatigue of operators.

This study considers the importance of human factors in picking activities such as physical fatigue of operators and the need to have validated tools to monitor and to define the level of fatigue accumulation in each activity of different rate and duration.

Automated flow line manufacturing systems are becoming more and more relevant in industry, especially in the food and beverage sector. Improving the efficiency of automated flow line manufacturing systems is the core objectives of all companies as measured by the overall equipment effectiveness (OEE) index. The purpose of this paper is to carry out an innovative micro downtime data collection and statistical analysis in the food and beverage sector; it introduces a numerical indicator called “Cost Performance Indicator-CPI” to estimate the performance improvement of investment activities. Moreover this analysis will be used as a basis to carry out a new simulative model to study micro downtime of automatic production lines. In addition, the presented micro downtime data collection and statistical analysis will be used to construct a new simulative model to support improvement activities.

Descriptive and statistical analyses are carried out about OEE, time to repair (TTR) and time to failure (TTF) data. The least efficient production line is identified and principal causes of inefficiency are investigated. Micro downtime (downtime lower than 15 minutes) covers 57 percent of inefficiency. Investigations are carried out into the three principal machines affected by this inefficiency. The study then investigates the causes of micro downtime of these machines using ad hoc data collection and analysis. The probability distributions of TTF and TTR are evaluated and an analysis of micro downtime causes and a cause-effect is carried out. The most attractive investment in terms of recoverable OEE (1.44 percent) and costs is analyzed through the calculation of a CPI. One of the conclusions is to recommend the introduction of a payback period with a variable contribution margin.

This study get the basis for the construction of a new simulative model based on ad hoc micro downtime probability distributions, applied in automated flow line manufacturing systems. It gives an effort to downtime analysis in automated production lines and a guideline for future analysis. Results of this study can be generalized and extended to other similar cases, in order to study similar micro downtime inefficiency of other production lines. The statistical analysis developed could also potentially be used to further investigate the relationship between the reliability of specific machines and that of the entire line.

The case study presents a new detailed micro downtime data collection and statistical analysis in the beverage sector with the application of a numerical indicator, the CPI, in order to drive future actions. In addition, the presented micro downtime data collection and statistical analysis will be used to construct a new simulative model to support improvement activities. Moreover, results can be generalized and used as a basis for other micro downtime analyses involving the main causes of inefficiency in automated production lines.

Personalization of products, mix variability and short time to market are the most important factors that have forced companies to a new form of organization during past years. A very common reply to this question is a lean organization based on flexibility of productive lines, reduction of storage and integration among company sections. In this context, quite differently from a traditional system, the maintenance function must work efficiently. Also the maintenance division must contribute to the success of the factory. Aims to introduce a methodology for a soft and tenable application of the principles of total productive maintenance (TPM) in Italian factories. The first step of the study is an explanation of the actual situation, usually based on traditional or on productive maintenance. After a brief introduction, focuses on TPM links with productive maintenance in order to suggest a method for TPM. Concludes with a real application of TPM in a big factory, with a description of a world leader in plant manufacturing for the ceramics industry.

Logisticians in the worldwide industry are frequently faced with the problem of measuring the total cost of holding inventories with simple and easy-to-use methodologies. The purpose of this paper is to look at the problem, and in particular illustrate the inventory holding cost rate computation, when different kind of warehousing systems are applied.

A multiple case study analysis is here developed and supported by a methodological framework directly derived from the working group discussions and brainstorming activities. Two different field of application are considered: one related to five companies with manual warehousing systems operating with traditional fork lift trucks; the other is among five companies operating with automated storage/retrieval systems (AS/RS) to store inventories.

The multi-case study helps to understand how the holding cost parameter is currently computed by industrial managers and how much the difference between manual and automated/automatic warehousing systems impacts on the inventory cost structure definition. The insights from the ten case studies provide evidence that the kind of storage system adopted inside the factory can impact on the holding cost rate computation and permit to derive important considerations.

The final aim of this work is to help industrial engineers and logisticians in correctly understanding the inventory costs involved in their systems and their cost structure. In addition, the multi-case analysis leads to considerations, to be applied in different industrial contexts. As other industrial applications are identified, they may be analyzed by using the presented methodology, and with aid from the data from this paper.

The relevance of this work is to help industrial engineers and logisticians in understanding correctly the inventory costs involved in their logistics systems and their cost structure. In addition, the multi-case analysis lead to interesting final considerations, easily to be applied in different industrial contexts. As other industrial applications are identified, they may be analyzed by using the methodology and extrapolating the data from this paper.

Warehouse picking is often referred to as the most labour-intensive, expensive and time consuming operation in manual warehouses. These factors are becoming even more crucial due to recent trends in manufacturing and warehousing requiring the processing of orders that are always smaller and needed in a shorter time. For this reason, in recent years more efficient and better performing systems have been developed, employing various technological solutions that can support pickers during their work. The purpose of this paper is to introduce a comparison of five paperless picking systems (i.e. barcodes handheld, RFID tags handheld, voice picking, traditional pick-to-light, RFID pick-to-light).

Warehouse picking is often referred to as the most labour-intensive, expensive and time consuming operation in manual warehouses. These factors are becoming even more crucial due to recent trends in manufacturing and warehousing requiring the processing of orders that are always smaller and needed in a shorter time. For this reason, in recent years more efficient and better performing systems have been developed, employing various technological solutions that can support pickers during their work. The present paper introduces a comparison of five paperless picking systems (i.e. barcodes handheld, RFID tags handheld, voice picking, traditional pick-to-light, RFID pick-to-light.

The proposed approach contributes to the understanding of the performance of different technologies in different application fields; some solutions are more suitable for a low-level warehouse, others bring greater benefits in the case of picking from multilevel shelving.

The study concerns an issue that until now has received very little attention in the literature. It compares some traditional solutions with some innovative ones by an economic evaluation. The presented hourly cost function also takes into account the different errors arising and their probability of occurrence.

The purpose of the present research is to explore the current situation and future expectations on whether to self‐manage or outsource logistics operations in centralized healthcare networks, and to analyse and quantify the relationships between logistics outsourcing, costs and performance.

The paper is based on a thorough study of a local Italian healthcare network, which evaluated the economic sustainability of logistics outsourcing. The data were collected using interviews, documentation and observations in hospital pharmacies and wards, and by referring to public information available on the internet. A system dynamic simulation followed by a sensitivity analysis was used to investigate the impact of changing key variables as well as the advice of logistics providers.

The sensitivity analysis demonstrates that logistics outsourcing is often the most economical choice.

Performance‐oriented concepts applied to healthcare have many pros in terms of sustainable delivery of quality healthcare at affordable costs.

While there are numerous studies on logistics outsourcing in many industries, when it comes to the healthcare sector literature is scarce, probably due to the great changes this sector has faced in recent times: thus, the paper's quantitative findings should be seen as a first attempt to assist the “make‐or‐buy” decision process toward sustainable development of the healthcare sector.

Recently, material flows have been viewed as an integral part of the overall manufacturing system and a critical factor in SCM. Static approaches and theoretical models are ineffective in considering all variables and constraints involved in complex instances: these often require a lot of computing time and present poor flexibility in terms of model changes. VIS approach is a valid way to support design and management decisions in order to achieve the integrated optimisation of the whole chain, but literature does not discuss difficulties and time required in applying it, or its related costs.

Discrete/continuous hybrid simulation tools are used in order to model and simulate several operating conditions in combination with different system configurations.

The discussion of the industrial cases shows the importance of simulation in supporting decisions concerning the design and management of supply chains in their great complexity and in a stochastic competitive and extended context.

The paper deals with five significant industrial cases, which are simulated in collaboration with important enterprises and belong to different industrial sectors, in order to obtain an original quantitative analysis of time and costs resulting from a simulation optimisation based on the introduction of a set of innovative performance indices.

The purpose of this paper is to apply group assembly (GA) considerations to the construction industry and to provide evidence of construction sector industrialization with quantitative results. Moreover, a flexible assembly system is proposed, especially designed to cope with variability: this can be easily extendable to other industrial sectors, especially when dealing with extremely variable environments.

The paper presents a case study conducted at an Italian company leader in the design, manufacture and installation of architectural claddings and lightweight continuous facades.

The research empirically demonstrates how the application of GA and the creation of project families lead to consistent enhancement also within the construction industry. The case study reveals great improvement in terms of both operating and ergonomic performances, agile assembly system reconfiguration design and make span reduction. The possibility of correlating a new project to an identified family gives the opportunity to understand the best assembly line layout configuration which should be assigned to the project, to improve the throughput time and the controllability of the assembly process and to guarantee efficient floor space utilization, lead‐time control, accuracy and reliability.

The novelty of the study lies in the way the assembly layout is designed to cope with variability: the assembly line, which is dedicated to more stable processes, is coupled with pre‐assembly stations, easily reconfigurable, meant to be “variability absorbers”. As far as the authors know, this is also the first time GA is applied to the construction industry. Moreover, a timely topic such as construction sector industrialization is confirmed by quantitative results.

Versatile manufacturing (VM) companies typically manufacture high variety, mainly customised products in relatively low volumes, competing for each order with other supplier companies on the basis of price, technical expertise, delivery time and punctuality. The research presented in this study is included in a wide cross‐disciplinary project which involved seven research centres. In particular, this paper aims at identifying the general requirements and guidelines for the definition of an integrated model of the order to delivery cycle in a VM environment, which can particularly be suitable for the small‐medium enterprise needs. A number of guidelines emerged, mainly in the areas of customer requirements definition and commercial configuration of customer order, supply and production planning, and intermediate and final project evaluation.