For decades three-dimensional (3D) measurements of engineering components have been made using fixed metrology-room based coordinate measuring machines (CMMs) fitted most commonly with single point or to a much lesser extent, scanning tactile probes. Over the past decade there has been a rapid uptake in development and subsequent use of portable optical-based 3D coordinate measuring systems. These optical-based systems capture vast quantities of point data in a very short time, often permitting freeform surfaces to be digitized. Documented standards, for example ISO 10360, for the verification of fixed CMMs fitted with tactile probes are now widely available, whereas verification procedures and more specifically verification artefacts for optical-based systems are still in their infancy. Furthermore, the industry is seeking traceability in 3D measurements of high precision components. A recent requirement is the demand for highly accurate measurements of large gears with diameters up to 1000 mm as used in gear boxes of wind turbines. Up until now it has been impossible to ensure traceability of 3D measurements of big gears, since no traceable standards were available. This paper describes three different types of artefacts that were developed during the project, namely tetrahedron artefacts for testing the basic measurement capability of optical 3D devices, freeform verification artefacts for testing the capability of measuring complex geometry, and a large gear artefact for task related calibration of different types of CMMs. In addition, artefact calibration data and associated measurement uncertainties and international intercomparisons are presented. These developments will be of considerable value to end users, calibration laboratories and producers of optical and tactile CMMs.

Sharing charging stations are an effective solution for daily usage of electric vehicles charging, however, the area with high demand cannot provide enough stations while there are plenty of stations left idle in remote areas with less demand. The core of the problem is the imbalance of demand and supply. In other word, we need to allocate the charging station to the appropriate locations to balance demand and supply. This study aims to solve the problem of locating charging stations for public electric vehicles (PUEVs), to improve the sharing charging level. We take into consideration the factors affecting charging station locations including mileage, PUEV distribution and passenger distribution. A Non-deterministic Polynomial (NP) model aiming to minimize the total vehicle service distance is developed. We use an agent-based model to simulate the optimized charging station location based on Anylogic. Through a case study of Beijing, we test the model in five situations. This paper concludes that priority, mileage, PUEV distribution and passenger distribution are the key factors affecting the location of PUEV charging stations, with exogenous variables such as the type of circuit and the voltage drawn as constants. The results of one situation show that the existing layout of the charging stations is unreasonable when charging frequency is sharply variant; this paper optimizes the existing location by improving the constraint for the smallest number of charging stations; the proposed model can be used for EV charging stations' location in densely populated metropolis.INDEX TERMS Agent, charging frequency, sharing charging, electric vehicles, location.

Manufacturers have to look constantly for new strategies and tools to improve processes, decrease cost and increase productivity and efficiency. Production scheduling is one of the crucial elements in manufacturing and has an impact on delivery deadlines and also on the production process in terms of its utilization. On the other hand, the value stream optimization is very important for lean manufacturing efforts. This paper is aimed to research the impact of job shop scheduling on value stream optimization and decreasing of cost-time investment. Value stream mapping represents a very efficient tool for visualization of activities within production flow focused on activity duration with the purpose to eliminate non-value added activities. Value stream costing is based on value stream and eliminates the need for overhead allocation and calculation. Cost-time profile is a powerful tool for visualization and calculation of cost accumulation during the time across the entire manufacturing flow. Software tools used in this paper are: Lekin scheduling system for constructing the schedules based on four different dispatching rules and Cost-Time Profiler software for simulating the impact of different schedules on total production cost and cost-time investment (representing the time value of money), which is proposed as a new scheduling objective function.

There has been an increasing call from academics specialising in operations management to integrate different strategic management perspectives into operations strategy research. Recently some pieces of operations strategy research have used the resource-based view. It is often suggested that the incorporation of resource-based view ideas into the ®eld of operations strategy is a search for a new paradigm, yet the ever-increasing literature suffers from a lack of empirical research. Moreover, operations strategy research from the evolutionary perspective, using longitudinal ®eld data, is almost completely neglected. This paper attempts to make two contributions. The ®rst is to stimulate debate about the incorporation of resource-based view and dynamic capabilities within operations strategy research. The second is to present a model based on in-depth ®eld research where the dynamics of the capability accumulation process is explored.

Multi-Objective (MO) optimization is a well-known research field with respect to the complexity of production planning and scheduling. In recent years, many different Evolutionary Computation (EC) methods have been applied successfully to MO production planning and scheduling. This paper is focused on making a review of MO production scheduling methods, starting from production scheduling presentation, notation and classification. The research field of EC methods is presented, then EC algorithms` classification is introduced for the purpose of production scheduling optimization. As a main goal, MO optimization is focused on hybrid EC methods, and presenting their advantages and limitations. Finally, a survey of five scientific databases is presented, with the analysis of the scientific publications the terminology development of the scientific field is presented. Using the citation analysis of the scientific publications, the application for the MO optimization in manufacturing scheduling is discussed.