Mikel Arcelus

Development of a wireless Plug&Lean system for improving manufacturing equipment diagnosis

Equipment efficiency can be measured and improved by the availability, performance and quality rates provided by the overall equipment effectiveness (OEE) metric. Because todays managers operate in a complex manufacturing scenario, measurement systems play an important role in transforming data into decisions, and this task needs to be strengthened. Although sophisticated equipment and information technology systems are available, a methodology is required for understanding and managing data in order to make timely decisions regarding improvement. Thus, improvement needs to be supported by an easy-to-understand measurement system and a cutting-edge data-collecting technique. In order to assist not only managers and operators but also students and academia, this article presents a Plug&Lean system supported by a core element, the Plug&Lean wireless device, based on total productivity maintenance (TPM) and Lean methodology for providing a reliable diagnosis of the current state of equipment, to display graphical information about the equipment performance constraints towards to direct improvements activities. The aim of the Plug and Lean wireless device is to collect accuracy data with less effort from production equipment Two case studies are discussed to illustrate the applicability of the system.

Teaching Theory of Constraints in 10 hours using open-source simulator

In this paper, the use of a graphical simulator called TOCNUN is presented. It helps users to understand plant operations conducted under the philosophy of Theory of Constraints (TOC) developed by Goldratt. TOCNUN is an alternative tool developed to support the teaching of TOC in just six or seven steps, which correspond to six or seven, 90-min learning sessions, including theory. This paper illustrates the structure for practical sessions that should be carried out with the simulator. Finally, validation input from undergraduate students and company managers is presented.

Assessing an Incubator Model in a Technological Centre: The Importance of the Spin-Off’s Origin

This paper proposes an assessment framework for a university incubator using eight criteria. This framework has been used with eight high-tech spin-offs incubated in CEIT (Spanish Technological Centre that was created by the University of Navarra), taken into account the point of view of their CEOs with interviews and a questionnaire. The results achieved can provide some useful indications to managers of University Business Incubators (UBIs). The incubator’s services demanded by the spin-off depend on several parameters, but the promoter profile of the new firm (a single person or the university itself) is a critical parameter.

Developing a Plug&Lean-CiMo a Model for Improving Manufacturing Operations

Manufacturers continue facing the never ending challenge of finding the best way to increase productivity levels in order to remain competitive. Significant level of productivity are given by the efficient utilization of production equipment, thus manufacturing companies use the overall equipment effectiveness (OEE) rate as an indicator to control equipment utilization related to the maintenance activity; however they do not take into account other valuable OEE-information to improve their entire manufacturing operations. This paper presents a continuous improvement model Plug&Lean-CiMo, whose aims are the accurate calculation of the OEE indicators, the appropriate classification of losses, and the systematic integration of lean manufacturing philosophy tools in an improvement methodology. The model has the advantage of using a portable wireless system to support the automated collection, of data to make the continuous improvement process easier. A case study is presented to illustrate the validation of the model.

A Framework Based on OEE and Wireless Technology for Improving Overall Manufacturing Operations

Manufacturers have the challenge to increase productivity given complex manufacturing environments. A source that provides substantial levels of productivity is the overall equipment effectiveness (OEE) metric, which is an indicator to improve not only equipment utilization; but also the overall manufacturing operations, because of the valuable information that comes from the availability, performance and quality rates. Although information technologies have been introduced, companies use manually recorder data and have complicated measurement procedures. As a consequence, inaccurate information is generated and opportunities to improve productivity are missed. This paper presents a continuous improvement framework based on Lean manufacturing philosophy, operated by a system of wireless devices to support the real time equipment performance metrics. In order to validate the framework, results of a case study are exposed.