A resource allocation method of the product−service process based on process mining

Abstract

With the evolution of product service systems, as well as the proposal and wide application of cloud computing and big services, more and more manufacturing enterprises are turning from being product oriented to service oriented. A difficult aspect is that with the growth of customer scale and the personalization of customer service needs, service providers cannot rely on their own resources to fulfill services. Moreover, meeting the needs of customers often requires a complete and complex service. Therefore, the service provider has to provide cross-enterprise collaborative services and coordinate the resources of all participants in the product service system to complete the services together. This research proposes a novel resource allocation method for product service systems that adopt the bilateral resource integration service mode and considers the service process life cycle. Based on the process mining techniques, this method extracts knowledge from the execution event log of the service process stored in the enterprise information system, constructs the resource allocation problem model, and gives the process mining-based resource allocation algorithm (PMRA). We use an air conditioner repair service as a case to verify the method proposed in this study. The contribution of this study is to propose a new method of resource allocation for cross-enterprise product−service processes based on process mining techniques, which takes into account empirical knowledge from historical data and can provide a new idea for service optimization of product service systems.

Pixel‐Level Grayscale Manipulation to Improve Accuracy in Digital Light Processing 3D Printing

“…Optical lens can be used to adjust the projected pixel size, resulting in resolution from 7.6 [ 13,14 ] to 250 µm. [ 15 ] DLP has been employed in many functional applications including soft robotics, [ 16,17 ] printed electronics, [ 18,19 ] metamaterials, [ 20–22 ] and 4D printing. [ 23,24 ]…”

“…Optical lens can be used to adjust the projected pixel size, resulting in resolution from 7.6 [13,14] to 250 µm. [15] DLP has been employed in many functional applications including soft robotics, [16,17] printed electronics, [18,19] metamaterials, [20][21][22] and 4D printing. [23,24] Recent advances in DLP have also allowed for the fabrication of structures with locally varying mechanical properties by controlling the light intensity (or so-called grayscale intensity).…”

“…This is known as overcuring, which reduces the achievable resolution. [15,[32][33][34] In addition, each pixel has a square shape, so printing features of rounded or angled shapes will lead to a stair step effect. [33,35] The combination of these effects can lead to unwanted artifacts in the final printed geometry.…”