Farm Safety Net Programs: Background and Issues

The U.S. Department of Agriculture (USDA) operates several programs that supplement the income of farmers and ranchers in times of low farm prices and natural disasters. Federal crop insurance, farm programs, and disaster assistance are collectively called the farm safety net. Federal crop insurance is often referred to as the centerpiece of the farm safety net because of its cost and broad scope for addressing natural disasters. The program is permanently authorized and makes available subsidized insurance for more than 130 commodities (ranging from apples to wheat) to help farmers manage risks associated with a loss in yield or revenue. Program cost is projected by the Congressional Budget Office to total $8.8 billion per year over the next decade. Producers pay a portion of the premium which increases as the level of coverage rises. The federal government pays the rest of the premium—62Farm commodity programs historically represented the heart of U.S. farm policy by virtue of their long history (dating back to the 1930s). Price and income support is based primarily on statutorily fixed prices and not market prices (as in crop insurance), which can be quite low in some years. For crop years 2014-2018, the Agricultural Act of 2014 (2014 farm bill, P.L. 113-79) established minimum prices via the marketing loan program for approximately two dozen commodities, including corn, soybeans, wheat, rice, and peanuts. In addition, producers with production histories for covered crops have a one-time choice between Price Loss Coverage (PLC) payments and Agriculture Risk Coverage (ARC) payments. Costs were projected in March 2015 at about$4 billion per year over the next decade. Programs are free for producers. Agricultural disaster assistance is permanently authorized for livestock and orchards. Under the 2014 farm bill, nearly all parts of the U.S. farm sector are now covered by either a disaster program or federal crop insurance, which is expected to reduce calls for ad hoc assistance. As of May 2015, producer payments had totaled more than $5 billion for losses in FY2012-FY2015. Compared with the previous farm bill, the 2014 farm bill was enacted with more crop insurance options and higher reference prices designed to trigger payments more often than under previous law. Funding was accomplished by eliminating direct payments that had been made annually since 1996 but played no role in managing farm risk because they did not vary with farm prices. Several facets of the current farm safety net might be of interest to the 114th Congress. An initial focus could be on USDA’s implementation of the farm safety net provisions. Issues could include the delayed payment schedule, which could expose cashflow problems, and the pending “actively engaged” rule that could affect program eligibility for some producers. With ongoing concern for budget deficits and federal spending, Congress also might be interested in reviewing the effectiveness of the revised safety net and actual costs, which are expected to be higher than earlier projections due to lower farm prices. Farm safety net proponents say the current suite of programs has been designed for such situations and is needed to adequately protect producers and the overall agriculture sector. Critics believe that a simplified approach might be more effective and less expensive, with funds used instead for broad societal gains, such as investment in agricultural research or transportation infrastructure. The Administration has proposed trimming crop insurance subsidies, arguing that the safety net could remain effective

Decision support for build-to-order supply chain management through multiobjective optimization

This paper aims to identify the gaps in decision-making support based on multiobjective optimization for build-to-order supply chain management (BTOSCM). To this end, it reviews the literature available on modelling build-to-order supply chains (BTO-SC) with the focus on adopting multiobjective optimization (MOO) techniques as a decision support tool. The literature has been classified based on the nature of the decisions in different part of the supply chain, and the key decision areas across a typical BTO-SC are discussed in detail. Available software packages suitable for supporting decision making in BTO supply chains are also identified and their related solutions are outlined. The gap between the modelling and optimization techniques developed in the literature and the decision support needed in practice are highlighted and future research directions to better exploit the decision support capabilities of MOO are proposed

Marketing Order Impact on the Organic Sector: Almonds, Kiwifruit and Winter Pears

Marketing,

Lessons Learned: Solutions for Workplace Safety and Health

Provides case studies of workplace health hazards, regulatory actions taken, and solutions, including product and design alternatives; a synthesis of findings and lessons learned; and federal- and state-level recommendations

Decision support for build-to-order supply chain management through multiobjective optimization

This is the post-print version of the final paper published in International Journal of Production Economics. The published article is available from the link below. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. Copyright @ 2010 Elsevier B.V.This paper aims to identify the gaps in decision-making support based on multiobjective optimization (MOO) for build-to-order supply chain management (BTO-SCM). To this end, it reviews the literature available on modelling build-to-order supply chains (BTO-SC) with the focus on adopting MOO techniques as a decision support tool. The literature has been classified based on the nature of the decisions in different part of the supply chain, and the key decision areas across a typical BTO-SC are discussed in detail. Available software packages suitable for supporting decision making in BTO supply chains are also identified and their related solutions are outlined. The gap between the modelling and optimization techniques developed in the literature and the decision support needed in practice are highlighted. Future research directions to better exploit the decision support capabilities of MOO are proposed. These include: reformulation of the extant optimization models with a MOO perspective, development of decision supports for interfaces not involving manufacturers, development of scenarios around service-based objectives, development of efficient solution tools, considering the interests of each supply chain party as a separate objective to account for fair treatment of their requirements, and applying the existing methodologies on real-life data sets.Brunel Research Initiative and Enterprise Fund (BRIEF

Generic bill of functions, materials, and operations for SAP2 configuration

International audienceMost available studies on configuration focus on either sales configuration specifying functional features or production configuration addressing product components. It has been well recognised that automating most of the activities associated with specification, engineering, and process planning of customised products and their interactions is one key in achieving product customisation. Thus, treating sales configuration and product configuration separately may not contribute to product customisation from a systematic view although they may lead to the improvement of individual stages. Recognising this limitation of existing studies, in this paper, we propose integrated SAles, Product and Production (SAP2) configuration, which helps achieve product customisation from a holistic view. Its rationale lies in automating consistently sales, product and production configuration activities in one system. In view of the importance of configuration models, we focus on the model underpinning SAP2 configuration called generic bill of functions, materials and operations (GBoFMO) and discuss it in detail. As the core of SAP2 configuration, GBoFMO can provide companies with an insight into organising the large volumes of data and knowledge in the life cycle of product family development. We also report a case study of light passenger aircrafts to illustrate the GBoFMO

Energy from waste and the food processing industry

The provision of a secure, continuous energy supply is becoming an issue for all sectors of society and the foodprocessingindustry as a major energy user must address these issues. This paper identifies anaerobic digestion as an opportunity to go some way to achieving energy security in a sustainable manner. However, a number of energy management and waste reduction concepts must also be brought into play if the environmental, social and economic aspects of sustainability are to be balanced. The reporting of such activity will help to promote the green credentials of the industry. Cleaner production, supply chain and life cycle assessment approaches all have a part to play as tools supporting a new vision for integrated energy and waste management. Our reliance on high-energyprocessing, such as canning and freezing/chill storage, might also need re-assessment together with processing based on hurdle technology. Finally, the concepts of energy and power management for a distributed energy generation system must be brought into the foodprocessingindustry

Cloud-based manufacturing-as-a-service environment for customized products

This paper describes the paradigm of cloud-based services which are used to envisage a new generation of configurable manufacturing systems. Unlike previous approaches to mass customization (that simply reprogram individual machines to produce specific shapes) the system reported here is intended to enable the customized production of technologically complex products by dynamically configuring a manufacturing supply chain. In order to realize such a system, the resources (i.e. production capabilities) have to be designed to support collaboration throughout the whole production network, including their adaption to customer-specific production. The flexible service composition as well as the appropriate IT services required for its realization show many analogies with common cloud computing approaches. For this reason, this paper describes the motivation and challenges that are related to cloud-based manufacturing and illustrates emerging technologies supporting this vision byestablishing an appropriate Manufacturing-as-a-Service environment based on manufacturing service descriptions

Linking design and manufacturing domains via web-based and enterprise integration technologies

The manufacturing industry faces many challenges such as reducing time-to-market and cutting costs. In order to meet these increasing demands, effective methods are need to support the early product development stages by bridging the gap of communicating early design ideas and the evaluation of manufacturing performance. This paper introduces methods of linking design and manufacturing domains using disparate technologies. The combined technologies include knowledge management supporting for product lifecycle management (PLM) systems, enterprise resource planning (ERP) systems, aggregate process planning systems, workflow management and data exchange formats. A case study has been used to demonstrate the use of these technologies, illustrated by adding manufacturing knowledge to generate alternative early process plan which are in turn used by an ERP system to obtain and optimise a rough-cut capacity plan