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Purpose of this paper:
Image processing technology has gained much improvement in recent years. In smart warehousing, most focus is on warehouse operations to improve efficiency and save human labors. However, in put-away, re-warehousing or picking process, after being handled by forklifts or laborers, the stacking of inventory items may change its shape and balance due to deviation, compression, tilting, etc., which may jeopardize the safety of stored goods and even people working in the warehouse. If there is a system that could monitor the stacking of inventory items all the time and could alarm managers should the stacking tilts or deforms to a certain level, inventory safety could be vastly improved. This study is on smart warehouse safety problems emphasizing at goods stacking to avoid the possibility of falling or collapse through image processing via Mask R-CNN. Our experiment is limited to items that form a rectangular block on a pallet, such as wooden bars, cartons or any box-shaped items.
Design/methodology/approach STS:
Mask R-CNN is a deep learning software and can be used in a wide range of applications. In this study, we used Mask R-CNN to detect the images of stacked items to see if the stacking is stable. We took photos from a warehouse and divided them into three classes – training, validation and production. VGG Image Annotator (VIA) was used for object annotation. To detect the tilt degree of stacked items, we derived formulation from book- stacking problems and retrieved dot coordinates of square frames encompassing objects in an image from the result of Mask R-CNN for calculation.
Findings:
Because there is a limited number of photos for training, validation and production, we applied image enhancement techniques such as flipping, affinity, multiplication, etc. to increase the total number of images to avoid over-fitting during the training process. The trained Mask R-CNN network demonstrated its capability in framing objects and after retrieving the dot coordinates of the frames, it could compute the degree of tilt as a reference for block stacking alarm.
Value:
The paper presents a relatively rare study of applying deep learning techniques on images as applied to material stacking safety problems. It contributes to a special smart warehousing domain. The same technique can be applied to inventory counting and help improve labor-saving in counting and in locating items in a warehouse.
Research limitations/implications:
Due to the limited number of images and restricted angles of taking the images, Mask R- CNN may not be so capable in framing objects of special angles of images. More images with diverse angles of them should be obtained for training to improve the capability of the trained network.
Practical implications:
Successful implementation of the technology developed in this study in a warehouse monitoring system can help industries in smart detection of improper stacking to assist human in improving the accuracy of safety judgement and can also save labors in reviewing images or records of a warehouse.
Leicht verständlich und sehr übersichtlich mit Hilfe einer praxisorientierten Beschreibung werden die relevanten Grundlagen des Qualitätsmanagements dargestellt. Dabei wird der Bogen von den elementaren Qualitätswerkzeugen über die klassischen Qualitätsmethoden bis zum umfassenden Qualitätsmanagement TQM gespannt. Somit erwirbt sich der Leser einen guten Überblick über die Thematik. Verständnisfragen und Übungsaufgaben ermöglichen leicht ein Selbststudium. In der aktuellen Auflage wurde die Anzahl der Übungsaufgaben erhöht und ein Abschnitt über die aktuelle DIN EN ISO 9001-2015 aufgenommen.
Unternehmerisches Denken und Handeln kann in klassischen Lehrveranstaltungsformatennur eingeschränkt vermittelt werden. Dieser Beitrag erweitert das Modell der Juniorenfirma auf dem Sektor der beruflichen Bildung für den Einsatz in der akademischen Ausbildung. Das handlungsorientierte LearnFab-Konzept, das hier vorgestellt werden soll, ermöglicht Studierenden durch die vollständige Übernahme von operativer und strategischer Verantwortung für ein Unternehmen erfahrungsbasiertes Lernen, das durch systemisches Coaching unterstützt wird. Der Beitrag ordnet das LearnFab-Konzept in die handlungsorientierte Didaktik der Gründerausbildung ein und beschreibt dessen Konstruktion sowie erste Erfahrungen bei der Implementierung.
Taiwan has developed over the last two decades from a low-wages mass producer to a high-tech service economy. It has shown a sustainable economic growth during the last 8 years (excluding the crisis year of 2009) Due to its advanced health and education system and other factors it seems to be well prepared for the future. This is also shown in the current World Economic Forum Global Competiveness Report that calculates a Global Competitiveness Index by considering 12 different factors, such as Infrastructure, Higher Education and Innovation. Taiwan is listed in 13th place out of a total of 139 global economies. This equates to rank 3 among Asian countries (only Singapore and Hong Kong are ranked better)[1]. After having signed the Economic Cooperation Framework Agreement (ECFA) between Taiwan (Republic of China, ROC) and China (People's Republic of China, PRC) on 29th June 2010, R.O.C.’s economic and its political future is being currently reassessed by many foreign observers. The agreement, which has been in force since the first of January, 2011, opens new prospects for Taiwan to develop further Free Trade Agreements. China will definitely be one of the three biggest growth markets of the world's economic future in the upcoming decade. Therefore, a possible future status of Taiwan is to take the role as an "Asian Economic and Cultural Hub" for companies to gain a foothold into the Chinese or the entire Asian market. Taiwan already provides competitive attributes such as infrastructure, political and social stability as well as sophisticated business networks and cultural tolerance among other strengths, which characterizes it as an expanding potential partner and a possible link to Chinese Market.
While the world is struggling with shortage of fossil fuels energy and seeking for alternatives to it over the past several years, experts and investors have already identified renewable energy as alternative energies for fossil fuels and nuclear power. Among different types of energies, solar energy is considered as one of the most environmental friendly source. Not to mention that investment in solar photovoltaic (PV) industry had become a boom especially after the 21st century. However, due to the volatile of demand and changing patterns in manufacturing and distribution between several countries, the industry started to collapse. For this reason, many of PV related companies eventually have gone bankruptcy. Several methods, such as efficiency, responsiveness and agility, which are used to measure competitive factors for a company, have already been widely applied. Nevertheless adaptability is still a new and largely unexplored area. As a result, our research aims to develop a mechanism to measure supply chain adaptability under radical environment by building up case studies and extracting potential elements for metrics of solar PV industry. Qualitative research is conducted as our methodology, which combined with company reports, industry statistics, literature review and six semi-structured interviews with solar energy related companies in Germany. In our case studies, six companies specialize in different aspects of solar PV supply chain and demonstrate different emphasis regarding the adaptability of supply chain. Based on our result, company could assess their individual contributions and evaluate what abilities they are insufficient for preventing the risks involved when encountering volatile changes in the market.
Most research in the past mainly considers AS/RS in distribution environment. In this study, we consider AS/RS in the support of an assembly line having multiple cells. For the coordination between the assembly line and the AS/RS, we implemented metaheuristics with Tabu algorithm to solve the sequencing of tasks having picking and put-away operations in support of a Toyota manufacturing system where production lines are composed of cells to assemble simultaneously a variety of products such as auto parts, electronic devices, etc. In this paper, three Tabu heuristic algorithms were devised with variations in search and exchange. The first algorithm (TI) is a regular Tabu search with special initial solution strategy; the second algorithm (TID) combines TI with divide and conquer search strategy; the third algorithm (TIE) is TI with special exchange strategy. We experimented on an AS/RS – production system having 40 assembly cells and an AS/RS with capacity of 1600 baskets for holding materials for assembly. By making 30 runs for each of the above three algorithms, we found that that TIE performs the best, followed by TID and then TI. It also demonstrates that Tabu search can help the operation of AS/RS by reducing 5-30% of shop floor assembly time while TIE can obtain a sequence solution in the best possible time by saving 54.9% of the computation time over TI.
Recent risk incidents, such as 911 attacks, financial crisis, catastrophic disasters like earthquakes and floods, etc. have added challenges and susceptibility for business operations. In encountering more frequent and unpredictable risks than before, many companies adopt risk management systems and redesign their supply chain (SC) structures for stronger SC resilience as well as quicker recovery speed. In this paper, we present a case study of a large semiconductor packaging and testing company in Taiwan, AKH, in confronting risk incidents and the plans they implemented to strengthen the SC resilience to assure more reliable supply of their products and services to the customers worldwide. AKH executed several de-risking plans, which can be divided into four Rs - resourcefulness, redundancy, robustness and rapidity. Many of the de-risking plans rely on the E-Hub system the company implemented a few years ago for SC information visibility. After carrying out the de-risking plans, AKH found that the suppliers and customers as well as the company have to furnish additional kinds of information to the E-Hub system in order to improve the SC resilience and assess the impacts of risk incidents. The results show improved SC resilience for the case company in encountering risk incidents and much faster recovery speed once an incident occu
Dieses Lehr- und Fachbuch stellt sehr übersichtlich und leicht verständlich die Grundlagen des Qualitätsmanagements dar. Dabei wird der Bogen von den elementaren Qualitätswerkzeugen über die klassischen Qualitätsmethoden bis zum umfassenden Qualitätsmanagement TQM gespannt. Zahlreiche Verständnisfragen und Übungsaufgaben mit Lösungen sowie eine praxisorientierte Beschreibung ermöglichen leicht ein Selbststudium.
Purpose:
Generic business process models for the supply chain do not cover the specific requirements of the cold chain catering to the needs of temperature-sensitive, perishable goods. The purpose of this paper is to draft a reference model specific to the cold chain.
Design/methodology/approach:
Following an object-oriented modeling approach, conceptual elements that have been synthesized from a literature review are transferred into the static view (object model) of the reference model. In addition, the reference model’s dynamic properties representing the business process view are outlined.
Findings:
While a few atomic process steps are sufficient to model the cold chain’s dynamic properties, the complexity of the cold chain lies in the object model. The classes of the object model are highly interrelated and cover four domains: perishable product, information technology, infrastructure/equipment and regulatory framework. This technical approach is more adequate to the complex nature of cold chains than typical business process models.
Research limitations/implications:
In the present draft status, the reference model is limited by the pure conceptual approach of this paper. As it is in the nature of things for a draft of a reference model, case studies to challenge the draft and a discourse of experts are required before detailed specifications can be added or any software implementation can be started. It is expected that the reference model is able to substantially support further research on cold chain design and optimization.
Practical implications:
The cold chain reference model is intended to be a standard toolbox for planning and evaluating cold chains. By integrating the technical, information technology and regulatory objects behind the business processes, it allows to design and analyze cold chains from a more holistic perspective.
Originality/value:
To the best knowledge of the author, this paper is the first to outline a reference model for the cold chain that goes beyond the business processes.